CN103529704A - Skeletal muscle linear netlike array type artificial muscle design and artificial nerve control method - Google Patents

Abstract

The invention establishes a novel array type artificial muscle structural mode by simulating the microstructure of a skeletal muscle on the basis of an engineering bionics principle and deep microscopic analysis of the physical constitution and driving mechanism of an animal skeletal muscle, and stresses on the design of an artificial muscle driving process and a control method according to the structural characteristics of the skeletal muscle in combination of the control driving ways of the skeletal muscle microstructure and a nerve system on the skeletal muscle. According to the method, the artificial muscle is closer to a biological skeletal muscle on the aspects of structure, motion form, control method, driving process and the like.

Description

The netted array artificial-muscle design of class skeletal muscle straight line and the neural control method of class

Technical field

The present invention relates to robot Driving technique and bionics techniques, particularly relate to the neural control method of a kind skeletal muscle straight line netted array artificial-muscle construction design method and class thereof.

Background technology

Along with legged type robot application more and more widely under the occasions such as battlefield, anti-terrorism, rescue, space exploration, hazardous environment operation, the jump of robot, run, leaping over obstacles, steadily exercise performance and anti-foreign impacts and the complex-terrain adaptive faculty such as advance causes people's attention gradually.Thus, the performances such as instantaneous moment, hunting frequency and power density to joint of robot have proposed more and more higher requirement, and the type of drive of joint of robot generally adopts at present " electric rotating machine+gear train " is because being subject to the restriction of the power-acceleration characteristic of motor itself and the dynamics of gear train, be difficult to meet the requirement of military and civilian complicated applications environment to high-performance joint motions, the aspects such as, redundancy large in the urgent need to instantaneous acceleration is strong, fast response time and power density height have the next-generation drive of superior function.

The joint of animal that skeletal muscle drives is compactness simple for structure not only, at aspects such as energy storage, surge capability, speed, agility, energy density, prompt explosion power, there is the performance that traditional articulated driving equipment is difficult to reach simultaneously, the human body knee joint that is no more than 1Kg as weight can provide 10 times to the driving force of human body weight, the running speed of cheetah is up to 130 kilometers of speed per hours, and the biting force of esturaine crocodile approaches 1900Kg.Animals skeletal muscle has logical hierarchical architecture, and the size of initiatively shrinking the deflection that produces and power output is comprised of its interior microscopic that structure is common to have cooperated.This level structure makes animals skeletal muscle have highly redundant, even fraction microstructure is because the reasons such as damage, pathology can not be worked in skeletal muscle, to entire effect little.The hierarchical architecture of skeletal muscle makes skeletal muscle also have the features such as instantaneous acceleration is large, fast response time, the coordination ability is strong, agility is high, self-regulation structure parameter.Skeletal muscle has a lot of excellent properties as vertebrate motion muscle, use bionics principle, simulate the structure of biological skeletal muscle and artificial-muscle and the driving governor thereof of expulsion mechanism design, can obtain excellent properties and the concision and compact structure of biological skeletal muscle.

Most of artificial muscle be take muscle group power output, displacement and control method as human simulation object now, and less skeletal muscle micromechanism and micromanagement expulsion mechanism thereof is analyzed and research.Simulated animal bone machine hierarchical architecture carries out artificial-muscle Model Design, can make artificial-muscle have good redundancy and better serviceability.These problems that exist for modern driver, the present invention simulates skeletal muscle micromechanism, a kind of linear array formula artificial-muscle tactic pattern is proposed, it is more pressed close at the aspects such as structure, forms of motion, control method, driving process and biological skeletal muscle, have that instantaneous acceleration is large, redundancy good, the coordination ability is strong, fast response time and a power density high.

Summary of the invention

For driver in prior art, exist the performances such as redundancy, instantaneous moment, hunting frequency and power density can not meet the problem of modern machines people needs, the invention provides the netted array artificial-muscle design of class skeletal muscle straight line and the neural control method of class.

In order to realize above-mentioned task, the present invention adopts following technical solution:

The method for designing of the netted array artificial-muscle of one kind skeletal muscle straight line, the method comprises a plurality of class half muscle segment drivers by the netted array artificial-muscle of class skeletal muscle straight line, a plurality of class half muscle segment drivers form class muscle fibril driver through series connection, the class muscle fibril driver of take is symcenter, other class muscle fibril drivers are arranged side by side and formed the netted symmetric array formula of hexagonal honeycomb structure, same layer class half muscle segment driver on each class muscle fibril driver aggregates into one by class sarolemma connector by all class muscle fibril drivers respectively, and at polymerization all-in-one-piece class muscle fibril driver two ends, be provided with class aponeurosis (aponeuroses) connector and form artificial-muscle, the columns m of the netted array artificial-muscle of such skeletal muscle straight line and number of plies n determine by following technical step:

(1) according to artificial-muscle application and applied environment, provide maximum target output displacement L _asmaxand artificial-muscle when motion the maximum target power output F that needs _asmax;

(2) calculate artificial-muscle parallel-connection and count layer by layer n, n is natural number, if the maximum output displacement of class half muscle segment driver is x _smax, have

$\frac{L_{\mathrm{as}\max }}{x_{s\max }}\&le;n<\frac{L_{\mathrm{as}\max }}{x_{s\max }}+1---\left(1\right)$

(3) calculate the minimum columns k of artificial-muscle series connection layer, k is natural number, if the minimum power output f of class half muscle segment driver _smin, have

$\frac{F_{\mathrm{as}\max }}{f_{s\min }}\&le;k<\frac{f_{\mathrm{as}\max }}{f_{s\min }}+1---\left(2\right)$

(4) calculate netted hexagonal number of total coils c (c is natural number) in artificial-muscle series connection layer, c need meet following formula

$1+6\&CenterDot;\underset{i=2}{\overset{c-1}{\mathrm{\&Sigma;}}}(i-2)\&le;k\&le;1+6\&CenterDot;\underset{i=2}{\overset{c}{\mathrm{\&Sigma;}}}(i-2)---\left(3\right)$

(5) finally determine that artificial-muscle array architecture is columns

m is natural number, the number of plies $n=\frac{L_{\mathrm{as}\max }}{x_{s\max }}.$

The present invention also has following other technologies feature:

Same layer class half muscle segment driver on each described class muscle fibril driver aggregates into one by class sarolemma connector by all class muscle fibril drivers respectively, and all kinds of sarolemma connectors are successively equidistant arranges side by side.

At polymerization all-in-one-piece class muscle fibril driver two ends, be provided with class aponeurosis (aponeuroses) connector, class aponeurosis (aponeuroses) connector is hexagonal structure.

The neural control method of class of the netted array artificial-muscle of class skeletal muscle straight line of the present invention, comprises the steps:

The first step, in the control time Δ t resolving according to artificial-muscle upper strata controller, artificial-muscle target output displacement L _aswith and the target power output F in when motion _as;

Second step, advanced row artificial-muscle row are controlled, and calculate artificial-muscle parallel-connection key-course number of plies n, and n is natural number, if the maximum output displacement of class half muscle segment driver is x _smax, have

$\frac{L_{\mathrm{as}}}{x_{s\max }}\&le;n<\frac{L_{\mathrm{as}}}{x_{s\max }}+1---\left(4\right)$

The 3rd step, selects key-course according to power output minimum principle, and while moving according to artificial-muscle, the kinetics equation of class half muscle segment driver, judges and in its motion process, produce electromagnetic force f _{s (j)}(electromagnetic force f _{s (i) (j)}for all classes half muscle segment driver in shunt layer j produces total electromagnetic force) monotonicity and work shift x thereof _sselect artificial-muscle key-course, if the electromagnetic force f that class half muscle segment driver produces _{s (j)}for Parallel Control, count layer by layer the increasing function of j, select work shift x _scan meet target output displacement L _as, and the shunt layer nearest apart from artificial-muscle starting point layer is key-course; Otherwise, if electromagnetic force f _{s (j)}during for the subtraction function of variable j, select work shift x _scan meet target output displacement L _as, and the shunt layer nearest apart from artificial-muscle stop layer is key-course;

The 4th step, in control time Δ t, in key-course, the output displacement of each class half muscle segment driver is artificial-muscle target output displacement L _as, the class half muscle segment driver in non-key-course is in self-locking state, no-output displacement;

The 5th step, carries out the capable control of artificial-muscle, the work shift x of real-time measure and control layer _s, determine the maximum power output f under this work shift _xmax(x _s);

$f_{\mathrm{xmsx}}\left(x_s\right)=f(x_s,I_{\max })=\frac{d{W}_m(x_s,I_{\mathrm{mas}})}{d{x}_s}=\frac{\&PartialD;}{\&PartialD;x_s}\left[{\&Integral;}_V{\&Integral;}_0^H(B\&CenterDot;\mathrm{dH})\mathrm{dV}\right]---\left(17\right)$

Wherein, I _maxfor the peak coil current of class half muscle segment driver, W _m(x _s, I _max) be magnetic field energy, x _sfor work shift, H is magnetic field intensity, and B is magnetic induction density, the integrating range that V is volume integral;

The 6th step, according to target power output F _asdetermine that artificial-muscle series connection layer activates number n _yneed to meet following formula

f _xmax(x _s)·(n _y-1)≤F _as≤f _xmax(x _s)·n _y (18)

The 7th step, belongs to centrosymmetric image according to the reticulate texture of artificial-muscle, adopts to activate to activate according to centrosymmetric mode, and by the summation of all activated artificial-muscle series connection layer power output, be artificial-muscle target power output F _as, every pair of artificial-muscle series connection layer class power output Central Symmetry equates;

The 8th step, passes to controller by each the class half muscle segment driver resolving, and by R-C power and Position Hybrid Control in submissive control, completes power and the displacement output task of artificial-muscle in the instruction cycle.

The present invention is based on engineering bionics principle, at microcosmic angle, analyse in depth on the basis of animals skeletal muscle physiology formation and expulsion mechanism, simulation skeletal muscle micromechanism, set up a kind of novel array artificial-muscle tactic pattern, and according to its design feature, the control type of drive to skeletal muscle in conjunction with skeletal muscle micromechanism and nervous system, key design driving process and the control method of artificial-muscle, this artificial-muscle is more pressed close at the aspects such as structure, forms of motion, control method, driving process and biological skeletal muscle.

Artificial-muscle of the present invention consists of class half muscle segment driver connection in series-parallel, and by gear train Direct Drive Robot, does not move, thereby it is high to have execution efficiency, and the life-span is long, and redundancy is good, fast response time, the feature such as instantaneous acceleration is large.

Accompanying drawing explanation

Fig. 1 is artificial-muscle connector and reticulate texture numbering thereof;

Fig. 2 is artificial-muscle wiring layout, and wherein 2-1 is class muscle fibril driver, and 2-2 is class aponeurosis (aponeuroses) connector, and 2-3 is that class half muscle segment drives gas, and 2-4 is class sarolemma connector;

Fig. 3 is artificial-muscle construction design method process flow diagram;

Fig. 4 is class sarolemma connector construction figure, and wherein 4-1 is connecting thread hole, and 4-2 is cylindrical hole;

Fig. 5 is class aponeurosis (aponeuroses) connector construction figure, and wherein 5-1 is connecting thread hole, and 5-2 is cylindrical hole, and 5-3 is hinge hole, 5-4 connecting link;

Fig. 6 is artificial-muscle antenna array control schematic diagram;

Fig. 7 is that detection position is from judging pick-up unit hardware structure diagram;

Fig. 8 is the neural control flow chart of artificial muscle's meat;

Fig. 9 is that artificial-muscle drives quadruped robot wiring layout;

Figure 10 is quadruped robot hip joint dynamics cycle simulation curve;

Figure 11 is quadruped robot hip joint artificial-muscle dynamics cycle simulation curve;

Figure 12 is artificial-muscle power output and output displacement conversion schematic diagram

Figure 13 is quadruped robot knee joint endoprosthesis angular motion mechanics cycle simulation curve;

Figure 14 is quadruped robot knee joint artificial-muscle dynamics cycle simulation curve.

The present invention is described in further detail for the embodiment providing below in conjunction with accompanying drawing and inventor.

Embodiment

1. class skeletal muscle straight line netted array artificial-muscle construction design method and redundancy analysis

For avoiding the repeatability of skeletal muscle traditional batch pattern on function and structure, the skeletal muscle half muscle segment connection in series-parallel tier array pattern of simplifying is proposed, bionical this structural design artificial-muscle connection in series-parallel array structure: class half muscle segment driver class muscle fibril in series driver, by class muscle fibril driver, by class aponeurosis (aponeuroses) connector, become the netted parallel connection of honeycomb fashion to form artificial-muscle again, its two ends are connected with robot links by class sarolemma connector.The linear electromagnetic class half muscle segment driver that it is good with controlling respective performances that artificial-muscle is selected exercise performance is minimum movement unit, its performance is referring to Li Jing, Qin Xiansheng, Zhang Xuefeng etc. linear electromagnetic drives the design studies of connection in series-parallel array artificial-muscle, China Mechanical Engineering, 23 (08): 883-887,2012.On the basis of artificial-muscle kinetic model, the control mechanism of simulation biological nervous system to skeletal muscle, the neural control method of derivation artificial muscle meat.

Artificial-muscle designs based on bionics principle, first will simplify analysis to biological skeletal muscle.Skeletal muscle can be divided into 5 layers from macroscopic view to microcosmic, is respectively skeletal muscle, and------muscle fibre---muscle fibril---half muscle segment because this tactic pattern has repeatability on function and structure, so need to be simplified processing during Bionic Design to muscle bundle.The structure of skeletal muscles of simplifying need to be simplified myoarchitecture level, retains again the groundwork structure of skeletal muscle.Owing to all being isolated and being connected by different sarolemmas between muscle fibril, between muscle fibre, between muscle bundle, sarolemma belongs to connective tissue, can not be by nervous system ACTIVE CONTROL, and its structure and function class seemingly, are processed therefore this part is compressed to merge.After simplification, skeletal muscle can be regarded as by muscle fibril and consists of sarolemma effect parallel connection, and muscle fibril is in series by sarcomere, and skeletal muscle can be regarded as by half muscle segment and consists of effect connection in series-parallel.

Artificial-muscle array form simulation skeletal muscle muscle fibril structural design is netted, as shown in Figure 1.The similar honeycomb of this structure, has high strength and high material space ratio.The class muscle fibril driver of definition in symcenter is numbering 1, in initial first lap, be centered around other 6 class muscle fibril drivers that have of class muscle fibril driver 1, their positions are the second circle, be followed successively by numbering 2 to 7(wherein number 2 in upper-right position by clockwise order).By that analogy, c circle (c is netted hexagonal number of total coils in artificial-muscle series connection layer) has 6 (c-1) individual class muscle fibril driver, by clockwise order, is followed successively by numbering

class muscle fibril drive number in upper-right position is

i>=2 wherein.

Referring to Fig. 2, the micromechanism that skeletal muscle is simplified in artificial-muscle simulation designs: class half muscle segment driver class muscle fibril in series driver, and class muscle fibril driver is by class sarolemma connector, referring to Fig. 3 formation in parallel artificial-muscle, described class sarolemma connector is hexagonal structure, in class sarolemma connector center, be provided with connecting thread hole 4-1, on six drift angles of class sarolemma connector, be respectively arranged with cylindrical hole 4-2.At two ends, polymerization all-in-one-piece class muscle fibril driver two ends, pass through class aponeurosis (aponeuroses) connector, referring to Fig. 4, be connected with robot links, described class aponeurosis (aponeuroses) connector is hexagonal structure, at class sarolemma connector center, two connecting link 5-4 have been arranged in parallel, on connecting link, be provided with hinge hole 5-3, on six drift angles of class sarolemma connector, be respectively arranged with cylindrical hole 5-2 and threaded connection hole 5-1, wherein threaded connection hole 5-1 is positioned at and connects in the middle of a cylindrical hole 5-2.

Wherein, the selection of class half muscle segment driver directly affects the exercise performance of artificial-muscle, and the class half muscle segment driver of straight line voice coil loudspeaker voice coil electromagnetic principle design (document Li Jing meets each other, Qin Xiansheng, Zhang Xuefeng etc. linear electromagnetic drives the design studies of connection in series-parallel array artificial-muscle, China Mechanical Engineering, 23 (08): 883-887,2012) at aspect of performances such as response speed, efficiency and power densities, but there is very large advantage, meet robot specific (special) requirements to artificial-muscle at aspects such as instantaneous accelerations.As shown in Figure 3, specific design process is as follows for artificial-muscle construction design method process flow diagram:

The first step, first estimates maximum target output displacement L according to artificial-muscle application and applied environment _asmaxand artificial-muscle when motion the maximum target power output F that needs _asmax;

Second step, it is natural number that calculating artificial-muscle parallel-connection is counted n(n layer by layer), if the maximum output displacement of class half muscle segment driver is x _smax, have

$\frac{L_{\mathrm{as}\max }}{x_{\mathrm{samx}}}\&le;n<\frac{L_{\mathrm{as}\max }}{x_{s\max }}+1---\left(1\right)$

The 3rd step, calculating the minimum columns k(k of artificial-muscle series connection layer is natural number), if the minimum power output f of class half muscle segment driver _smin, have

$\frac{F_{\mathrm{as}\max }}{f_{s\min }}\&le;k<\frac{F_{\mathrm{as}\max }}{f_{s\min }}+1---\left(2\right)$

The 4th step, calculating netted hexagonal number of total coils c(c in artificial-muscle series connection layer is natural number) need meet following formula

$1+6\&CenterDot;\underset{i=2}{\overset{c-1}{\mathrm{\&Sigma;}}}(i-2)\&le;k\&le;1+6\&CenterDot;\underset{i=2}{\overset{c}{\mathrm{\&Sigma;}}}(i-2)---\left(3\right)$

The 5th step, finally determines that artificial-muscle array architecture is columns

(m is natural number), the number of plies

This biomimetic features design, makes artificial-muscle have good redundancy, and some class half muscle segment drive corruption can not cause too much influence to artificial-muscle motion.As the class half muscle segment driver that is positioned at No. 2 position of j floor is because the reasons such as self-locking coil opens circuit are locked, can not move, this layer of class half muscle segment drives it all in self-locking state, this layer does not participate in displacement exporting change, other layer of change in displacement do not impacted, the quantitative change of artificial-muscle overall shrinkage is short, still can use within the specific limits.As the class half muscle segment driver moving coil that is positioned at No. 2 position of j floor open circuit cause cannot produce power output, for avoiding asymmetric because of output, can produce a moment of torsion, reduce the efficiency of artificial-muscle, get its class half muscle segment driver with No. 5 positions, floor Central Symmetry position when this floor motion, all the time in relative sliding state, therefore during this layer of change in displacement, No. 2 and No. 5 position no-output power, do not affect the work of other class half muscle segment drivers, the total power output of artificial-muscle diminishes, and still can work under certain condition, has guaranteed good redundancy.

2. the neural control method design of class

Artificial-muscle is controlled effect and is mainly manifested on power output and output displacement, and power output and output displacement are determined jointly by all class half muscle segment drivers.Artificial-muscle control object is: each class half muscle segment driver status, electromagnetism power output and output displacement.By the capable called after artificial-muscle series connection layer of artificial-muscle (being class muscle fibril driver), artificial-muscle row called after artificial-muscle parallel-connection layer, the layer if class half muscle segment driver is connected with j in i shunt layer, uses A (j, i) to represent, as shown in Figure 5.The length variations of artificial-muscle is equivalent to the summation (being the length variations of single class muscle fibril driver) that artificial-muscle parallel-connection layer changes, the control that artificial-muscle parallel-connection layer is carried out is called row and controls, its power output is equivalent to the sum total of artificial-muscle series connection layer power output, and the control that artificial-muscle series connection layer is carried out is called row and controls.

Artificial-muscle two ends are connected with robot links by class aponeurosis (aponeuroses) connector, and wherein movable less one end is called artificial-muscle starting point, and the artificial-muscle parallel-connection layer of close starting point is called artificial-muscle starting point layer; Otherwise movable larger one end is called artificial-muscle stop, the artificial-muscle parallel-connection layer of close starting point is called artificial-muscle stop layer.Referring to the design to class half muscle segment driver in list of references [3]: if class half muscle segment driver in self-locking state, under its contracting brake mechanism spring action, mover is relative with stator static, there is no power consumption; In non-self-locking state, band-type brake coil electricity, mover and stator can relative motions, and contracting brake mechanism consumes stationary electric.Class half muscle segment driver status comprehensively determines by ranks state, and its ranks state of a control is integrated as shown in Figure 6.

The first rank of advanced units state of a control of artificial-muscle is analyzed: the half muscle segment Drive Status of class in shunt layer is divided into self-locking state and non-self-locking state.Class half muscle segment driver band brake apparatus in self-locking state starts, and does not produce output displacement; Class half muscle segment driver band brake apparatus in non-self-locking state does not start, and produces initiatively power output.On the basis of row state analysis, the class half muscle segment driver in non-self-locking state is carried out to the analysis of row state of a control: class half muscle segment Drive Status in series connection layer is divided into state of activation and unactivated state.Class half muscle segment driver active slip in state of activation, can produce initiatively power output; The passive slip of class half muscle segment driver in unactivated state, does not produce initiatively power output.

Simulation skeletal muscle excitation-contraction coupling mechanism is controlled and is designed row: electrical excitation signal, from the joint input of nerve-skeletal muscle,, is controlled half muscle segment and shunk successively to myocyte depths unidirectional delivery by transverse tubule system.Therefore, at artificial-muscle place, find an artificial-muscle parallel-connection layer for controlling the first floor, from this layer, control other shunt layers and move successively.

The neural control flow chart of artificial muscle's meat is as shown in Figure 8:

The first step, in the control time Δ t resolving according to artificial-muscle upper strata controller, artificial-muscle target output displacement L _aswith and the target power output F in when motion _as;

Second step, advanced row artificial-muscle row are controlled, calculating artificial-muscle parallel-connection key-course number of plies n(n is natural number), if the maximum output displacement of class half muscle segment driver is x _smax, have

$\frac{L_{\mathrm{as}}}{x_{s\max }}\&le;n<\frac{L_{\mathrm{as}}}{x_{s\max }}+1---\left(4\right)$

The 3rd step, selects key-course according to power output minimum principle, and while moving according to artificial-muscle, the kinetics equation of class half muscle segment driver, judges and in its motion process, produce electromagnetic force f _{s (j)}monotonicity and work shift x thereof _sselect artificial-muscle key-course.If the electromagnetic force f that class half muscle segment driver produces _{s (j)}for Parallel Control, count layer by layer the increasing function of j, select work shift x _scan meet target output displacement L _as, and the shunt layer nearest apart from artificial-muscle starting point layer is key-course; Otherwise, if electromagnetic force f _{s (j)}during for the subtraction function of variable j, select work shift x _scan meet target output displacement L _as, and the shunt layer nearest apart from artificial-muscle stop layer is key-course;

The 4th step, in control time Δ t, in key-course, the output displacement of each class half muscle segment driver is artificial-muscle target output displacement L _as, the class half muscle segment driver in non-key-course is in self-locking state, no-output displacement;

The 5th step, carries out the capable control of artificial-muscle subsequently, the work shift x of real-time measure and control layer _s, determine the maximum power output f under this work shift _xmax(x _s).The electromagnetic force computation process of class half muscle segment driver output is as follows:

Class half muscle segment driver is work shift x _swith the function of working coil current i, suppose that coil current is that under the condition of definite value, magnetic field of permanent magnet is constant, solving of magnetic field force can be carried out model solution according to Magnetostatic Field Problems.Maxwell equation is the mathematical model for all macroscopical electromagnet phenomenons, is the basis of Theory of Electromagnetic Field, is also the starting point of the numerical analysis of all kinds Electromagnetic Field and calculating.By Ampere circuit law (being circuital law), be can be expressed as:

Wherein, H is magnetic field intensity, and J is conduction current density vector,

for displacement current density.And under static magnetic field condition, therefore there is ▽ * H=J, by Maxwell equation (being the principle of continuity of magnetic flux), be:

▽·B＝0 (6)

Because of the constitutive relation of electromagnetic field field amount, can derive again:

$H=\frac{B}{{\mathrm{\&mu;}}_r{\mathrm{\&mu;}}_0}---\left(7\right)$

μ wherein _rfor solving the relative permeability of material, μ ₀for permeability of vacuum, B is magnetic induction density.Introduce vector potential A, have:

B＝▽×A (8)

Can derive:

$J=\&dtri;\&times;(\frac{1}{{\mathrm{\&mu;}}_r{\mathrm{\&mu;}}_0}\&dtri;\&times;A)---\left(9\right)$

According to law of conservation of energy, input electric energy W _eequal magnetic field energy W _mwith the energy W that is input to mechanical port _emsum, has:

W _e＝W _m+W _em (10)

Utilize the principle of virtual work to calculate electromagnetic force, magnetic field energy is to be calculated and obtained by the potential function in magnetic field, and FEM (finite element) calculation can be expressed as:

$W_m=\frac{1}{2}{\&Integral;}_{V}B\&CenterDot;\mathrm{HdV}---\left(11\right)$

Adopt the principle of virtual work to calculate magnetostatic power, suppose under the effect of electromagnetic force, between mover and stator, occur relative displacement ds, coupled magnetic field energy theorem is write as the form of differential:

dW _e=dW _m+dW _em=dW _m+F _emds (12)

DW _e, dW _mwith dW _embe illustrated in the clean electric energy of input coupled field in time dt, magnetic field absorbs gross energy and the gross energy that is converted into mechanical energy, F _emfor the electromagnetic force of mechanical port output, s is the displacement of mechanical port output.

For solving of static magnetic field system problem, if system consists of n loop, in i loop, magnetic linkage is changed to d ψ _i, size of current is definite value I _i, dW _ethe energy that the induction electromotive force being produced for resisting magnetic linkage variation by power supply produces can be expressed as:

$d{W}_e=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{I}_i\frac{d{\mathrm{\&psi;}}_i}{\mathrm{dt}}\mathrm{dt}=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{I}_{i}d{\mathrm{\&psi;}}_i---\left(13\right)$

Consider that in i loop, size of current is definite value I _i(be dI _i=0), the increment of system stored energy is:

$W_m=\frac{1}{2}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{I}_{i}d{\mathrm{\&psi;}}_i+\frac{1}{2}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{\mathrm{\&psi;}}_{i}d{I}_i=\frac{1}{2}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{I}_{i}d{\mathrm{\&psi;}}_i=\frac{1}{2}d{W}_e---\left(14\right)$

According to coupled magnetic field energy differential formulas, can be expressed as:

$F_{\mathrm{em}}\mathrm{ds}=d{W}_e-d{W}_m=\frac{1}{2}d{W}_e=d{W}_m---\left(15\right)$

Coil current size is thought of as steady state value here for I(), W _m(x _s, i) be magnetic field energy.The electromagnetic field of class half muscle segment driver adopts infinite element boundary condition in the hope of determining solution, i.e. unlimited distance B _∞=0.According to the principle of virtual work, between mover and stator, there is not real displacement, therefore permanent magnet is at virtual displacement x _sthe suffered power of direction can be expressed as:

$f_s=f(x_s,I)=\frac{d{W}_m(x_s,I)}{d{x}_s}=\frac{\&PartialD;}{\&PartialD;x_s}\left[{\&Integral;}_V{\&Integral;}_0^H(B\&CenterDot;\mathrm{dH})\mathrm{dV}\right]---\left(16\right)$

Determine implementation displacement x _sunder maximum power output f _xmax(x _s) can be expressed as peak coil current I _maxthe electromagnetic force producing under (peak coil current is the rated operational current of class half muscle segment driver here, is determined by processing conditions, and under processing conditions restriction now, getting its rated operational current is 1A) condition.So maximum power output f _xmax(x _s) can be expressed as

$f_{x\max }\left(x_s\right)=f(x_s,I_{\mathrm{mas}})=\frac{d{W}_m(x_s,I_{\max })}{d{x}_s}=\frac{\&PartialD;}{\&PartialD;x_s}\left[{\&Integral;}_v{\&Integral;}_s^H(B\&CenterDot;\mathrm{dH})\mathrm{dV}\right]---\left(17\right)$

The 6th step, according to target power output F _asdetermine that artificial-muscle series connection layer activates number n _yneed to meet following formula

f _xmax(x _s)·(n _y-1)≤F _as≤f _xmax(x _s)·n _y (18)

The 7th step, the reticulate texture of artificial-muscle belongs to centrosymmetric image, in order to guarantee its job stability in operational process, activates and activates according to centrosymmetric mode.The summation of all activated artificial-muscle series connection layer power output is artificial-muscle target power output F _as, every pair of artificial-muscle series connection layer class power output Central Symmetry equates.

The 8th step, passes to controller by each the class half muscle segment driver resolving, and by the submissive control of R-C power displacement, completes power and the displacement output task of artificial-muscle in the instruction cycle.

3. application example

3.1 key-course application examples

Utilize artificial-muscle kinematical equation to select key-course application example, the system of selection of artificial-muscle being controlled to the first floor with a simple example is carried out.If class muscle fibril driver starting point is fixed, stop target power output size is definite value f _y0, target output absolute acceleration is a _ms0, target absolute velocity v _ms0, artificial-muscle target contracted length is Δ l _ms0if, only have a class half muscle segment driver j active slip to produce power output, other class half muscle segment driver is all in self-locking state.

The relative acceleration of class half muscle segment driver can be expressed as:

${\stackrel{\&CenterDot;\&CenterDot;}{x}}_{s\left(k\right)}=\left\{\begin{array}{c}{a}_{\mathrm{<figure-callout\; id="0"\; label="ms"\; filenames="HDA0000394926380000052.png,HDA0000394926380000072.png"\; state="\{\{state\}\}">ms</figure-callout>}0},k=\mathrm{<figure-callout\; id="0"\; label="j"\; filenames="HDA0000394926380000052.png,HDA0000394926380000072.png"\; state="\{\{state\}\}">j</figure-callout>}\\ 0,k\&NotEqual;j\end{array}\right.---\left(19\right)$

The relative velocity of class half muscle segment driver can be expressed as:

${\stackrel{\&CenterDot;}{x}}_{s\left(k\right)}=\left\{\begin{array}{c}{\mathrm{<figure-callout\; id="0"\; label="v\; ms"\; filenames="HDA0000394926380000052.png,HDA0000394926380000072.png"\; state="\{\{state\}\}">v</figure-callout>}}_{\mathrm{ms}},k=\mathrm{<figure-callout\; id="0"\; label="j"\; filenames="HDA0000394926380000052.png,HDA0000394926380000072.png"\; state="\{\{state\}\}">j</figure-callout>}\\ 0,k\&NotEqual;j\end{array}\right.---\left(20\right)$

By principle of dynamics, derive the electromagnetic force size f that class half muscle segment driver need to produce _{s (i)}for:

$f_{s\left(i\right)}=f_{y0}-\underset{q=j}{\overset{n}{\mathrm{\&Sigma;}}}{f}_{\mathrm{ests}\left(q\right)}+(n-j)\&CenterDot;M\&CenterDot;{\stackrel{\&CenterDot;\&CenterDot;}{x}}_{s\left(j\right)}+m_a{\stackrel{\&CenterDot;\&CenterDot;}{x}}_{s\left(j\right)}---\left(21\right)$

Class half muscle segment driver is when reality is used, except the M.E. that produces between the suffered external force in two ends and mover and stator, (selection by artificial-muscle determines, the pressure producing such as electromagnetic force, air pressure and hydraulic pressure etc.) outside impact, the joint effect of the power such as the gravity that also can be subject to self producing, centripetal force, coriolis force, friction force.By self producing, except M.E., be referred to as effectively other power f _{extx (q)}.Wherein, M is class half muscle segment driver gross mass, m _afor mover part quality.

Complete goal task, consumption mechanical energy is the smaller the better, due to mechanical energy W _mecbe expressed as:

W _mec＝f _s( _j)·Δl _ms0 (22)

Due to target contracted length Δ l _ms0for definite value, the electromagnetic force that class half muscle segment driver j active slip produces is the smaller the better.For the punctured position of judgement class half muscle segment driver the best, diverse location electromagnetic force creates a difference and discusses.If completing the required generation electromagnetic force of goal task class half muscle segment driver j is f _{s (j)}, and the required generation electromagnetic force of class half muscle segment driver j-1 is f _{s (j-1)}, contrast f _{s (j)}with f _{s (j-1)}have:

$f_{s\left(j\right)}-f_{s(j-1)}=f_{\mathrm{ests}(j-1)}-M\&CenterDot;{\stackrel{\&CenterDot;\&CenterDot;}{x}}_{s(j-1)}---\left(23\right)$

While completing goal task, when

time, the electromagnetic force of the required generation of class half muscle segment driver is greater than the required generation electromagnetic force of class half muscle segment driver j-1, i.e. f _{s (j)}for the increasing function of variable j, thereby the electromagnetic force that class half muscle segment driver 1 active slip produces is the required minimum electromagnetic force of finishing the work; When

time, the electromagnetic force of the required generation of class half muscle segment driver j is less than the required generation electromagnetic force of class half muscle segment driver j-1, i.e. f _{s (j)}for the subtraction function of variable j, thereby the electromagnetic force that class half muscle segment driver n active slip produces is the required minimum electromagnetic force of finishing the work.

the application example of artificial-muscle on quadruped robot

With linear electromagnetic array artificial-muscle, replace electric rotating machine, for driving quadruped robot to move with diagonal gait, and leg exercise track is compared and analyzed, to verify the serviceability of class muscle driver.Quadruped robot adopts aluminum alloy materials to carry out simulation analysis, and Fig. 9 is shown in by quadruped robot ADAMS model.First the quadruped robot that adopts electric rotating machine to drive is carried out to the analysis of kinematics policy, the hip joint dynamics cycle simulation curve that obtains quadruped robot RAT simulation calculation is shown in Figure 10.Wherein, Figure 10-(a) is the joint angle temporal evolution curve of hip joint, Figure 10-(b) is the joint angle speed temporal evolution curve of hip joint, Figure 10-(c) is the joint angle acceleration temporal evolution curve of hip joint, and Figure 10-(d) is the output torque temporal evolution curve of hip joint.Quadruped robot RAT knee joint dynamics cycle simulation curve is shown in Figure 11.Figure 11-(a) is kneed joint angle temporal evolution curve, Figure 11-(b) is kneed joint angle speed temporal evolution curve, Figure 11-(c) is kneed joint angle acceleration temporal evolution curve, and Figure 11-(d) is kneed output torque temporal evolution curve.

If the right front foot of robot is used artificial-muscle to drive, other tripodias still adopt electric rotating machine to drive, by the following method can pre-estimation artificial-muscle power output scope and displacement range.Figure 12 is shown in by artificial-muscle power output and output displacement conversion schematic diagram.Angle between robot rod member normal is joint angle [234], and the intersection point between normal is articulation point.Definition articulation point is respectively l to the distance of artificial-muscle and rod member attachment point _g1with l _g2, articulation point is h to the distance of artificial-muscle _das, the angle between articulation point and artificial-muscle and rod member attachment point place straight line and rod member normal is respectively γ ₁with γ ₂, the angle of artificial-muscle two attachment points and articulation center is β.

When quadruped robot size and artificial-muscle attachment point are determined, l _g1, l _g2, γ ₁with γ ₂all fixed value, and Jch={ θ, ω, α, T} is input message, asks artificial-muscle information Mch={l _das, v _das, a _das, f _das.

Angle β can be expressed as:

β＝θ-γ ₁-γ ₂ (24)

Angular velocity

can be expressed as:

$\stackrel{\&CenterDot;}{\mathrm{\&beta;}}=\frac{\mathrm{d\&beta;}}{\mathrm{dt}}=\frac{d(\mathrm{\&theta;}-{\mathrm{\&gamma;}}_1-{\mathrm{\&gamma;}}_2)}{\mathrm{dt}}=\frac{\mathrm{d\&theta;}}{\mathrm{dt}}=\mathrm{\&omega;}---\left(25\right)$

Angular acceleration

can be expressed as:

$\stackrel{\&CenterDot;\&CenterDot;}{\mathrm{\&beta;}}=\frac{{\mathrm{<figure-callout\; id="2"\; label="d"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">d</figure-callout>}}^2\mathrm{\&beta;}}{\mathrm{<figure-callout\; id="2"\; label="d\; t"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">d</figure-callout>}{t}^{}{}^2}=\frac{d^2(\mathrm{\&theta;}-{\mathrm{\&gamma;}}_1-{\mathrm{\&gamma;}}_2)}{\mathrm{<figure-callout\; id="2"\; label="d\; t"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">d</figure-callout>}{t}^{}{}^2}=\frac{{\mathrm{<figure-callout\; id="2"\; label="d"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">d</figure-callout>}}^2\mathrm{\&theta;}}{\mathrm{<figure-callout\; id="2"\; label="d\; t"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">d</figure-callout>}{t}^{}{}^2}=\mathrm{\&alpha;}---\left(26\right)$

Articulation point is to the distance h of artificial-muscle _dascan be expressed as:

$h_{\mathrm{das}}=\frac{{\mathrm{<figure-callout\; id="1"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000052.png"\; state="\{\{state\}\}">l</figure-callout>}}_g\&CenterDot;{\mathrm{<figure-callout\; id="2"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">l</figure-callout>}}_g\&CenterDot;\sin \mathrm{\&beta;}}{l_{\mathrm{das}}}---\left(27\right)$

Artificial-muscle kinematic parameter modular converter calculates conversion, obtains artificial-muscle output displacement, output speed, output acceleration and power output, and these parameters are passed to bottom peripheral nervous system carries out artificial-muscle motion control.

Aggregative formula 24,25,26,27 and trigonometric function knowledge, can derive artificial-muscle output information Mch={l _das, v _das, a _das, f _dasexpression formula:

$\left\{\begin{array}{c}{l}_{\mathrm{das}}=\sqrt{{{\mathrm{<figure-callout\; id="1"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000052.png"\; state="\{\{state\}\}">l</figure-callout>}}_g}^2+{{\mathrm{<figure-callout\; id="2"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">l</figure-callout>}}_g}^2-2.{\mathrm{<figure-callout\; id="1"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000052.png"\; state="\{\{state\}\}">l</figure-callout>}}_g.{\mathrm{<figure-callout\; id="2"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">l</figure-callout>}}_g.\cos \mathrm{\&beta;}}\\ v_{\mathrm{das}}=\frac{{\mathrm{<figure-callout\; id="1"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000052.png"\; state="\{\{state\}\}">l</figure-callout>}}_g\&CenterDot;{\mathrm{<figure-callout\; id="2"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">l</figure-callout>}}_g\&CenterDot;\sin \mathrm{\&beta;}}{\sqrt{{{\mathrm{<figure-callout\; id="1"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000052.png"\; state="\{\{state\}\}">l</figure-callout>}}_g}^2+{{\mathrm{<figure-callout\; id="2"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">l</figure-callout>}}_g}^2-2\&CenterDot;{\mathrm{<figure-callout\; id="1"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000052.png"\; state="\{\{state\}\}">l</figure-callout>}}_g\&CenterDot;{\mathrm{<figure-callout\; id="2"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">l</figure-callout>}}_g\&CenterDot;\cos \mathrm{\&beta;}}}\\ a_{\mathrm{das}}=\frac{{\mathrm{<figure-callout\; id="1"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000052.png"\; state="\{\{state\}\}">l</figure-callout>}}_g\&CenterDot;{\mathrm{<figure-callout\; id="2"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">l</figure-callout>}}_g\&CenterDot;\cos \mathrm{\&beta;}\&CenterDot;({{\mathrm{<figure-callout\; id="1"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000052.png"\; state="\{\{state\}\}">l</figure-callout>}}_g}^2+{{\mathrm{<figure-callout\; id="2"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">l</figure-callout>}}_g}^2-{\mathrm{<figure-callout\; id="1"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000052.png"\; state="\{\{state\}\}">l</figure-callout>}}_g\&CenterDot;{\mathrm{<figure-callout\; id="2"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">l</figure-callout>}}_g\&CenterDot;\cos \mathrm{\&beta;})-{l^2}_{\mathrm{<figure-callout\; id="1"\; label="g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000052.png"\; state="\{\{state\}\}">g</figure-callout>}1}\&CenterDot;{l^2}_{g2}}{{({{\mathrm{<figure-callout\; id="1"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000052.png"\; state="\{\{state\}\}">l</figure-callout>}}_g}^2+{{\mathrm{<figure-callout\; id="2"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">l</figure-callout>}}_g}^2-2\&CenterDot;{\mathrm{<figure-callout\; id="1"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000052.png"\; state="\{\{state\}\}">l</figure-callout>}}_g\&CenterDot;{\mathrm{<figure-callout\; id="2"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">l</figure-callout>}}_g\&CenterDot;\cos \mathrm{\&beta;})}^{\frac{3}{2}}}\\ f_{\mathrm{das}}=\frac{T\&CenterDot;\sqrt{{{\mathrm{<figure-callout\; id="1"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000052.png"\; state="\{\{state\}\}">l</figure-callout>}}_g}^2+{{\mathrm{<figure-callout\; id="2"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">l</figure-callout>}}_g}^2-2\&CenterDot;{\mathrm{<figure-callout\; id="1"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000052.png"\; state="\{\{state\}\}">l</figure-callout>}}_g\&CenterDot;{\mathrm{<figure-callout\; id="2"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">l</figure-callout>}}_g\&CenterDot;\cos \mathrm{\&beta;}}}{{\mathrm{<figure-callout\; id="1"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000052.png"\; state="\{\{state\}\}">l</figure-callout>}}_g\&CenterDot;{\mathrm{<figure-callout\; id="2"\; label="l\; g"\; filenames="HDA0000394926380000011.png,HDA0000394926380000021.png"\; state="\{\{state\}\}">l</figure-callout>}}_g\&CenterDot;\sin \mathrm{\&beta;}}\end{array}\right.---\left(28\right)$

To pre-estimating robot quality, be 12～15kg, according to robot electric rotating machine curve of output, in conjunction with artificial-muscle installation site, estimate thigh power output scope at 70～100N, range of movement is between 115～200mm, shank power output scope is at 130～160N, and range of movement is between 100～140mm.According to estimated data, in conjunction with the maximum output displacement of class half muscle segment driver, be x _smax=16mm, minimum power output f _smin=2.8N, can calculate class half muscle segment drive array number in the artificial-muscle at robot thigh place is 37x6, in the artificial-muscle at robot shank place, class half muscle segment drive array number is 61x3.Therefore can calculate quadruped robot dynamics simulation parameter in Table 2.

Table 2 quadruped robot simulation parameter

Quadruped robot RAT hip joint artificial-muscle dynamics cycle simulation curve is shown in Figure 13.Figure 13-(a) is artificial muscle length temporal evolution curve, Figure 13-(b) is artificial contraction of muscle speed temporal evolution curve, Figure 13-(c) is artificial contraction of muscle acceleration temporal evolution curve, and Figure 13-(d) is power output temporal evolution curve.The kneed artificial-muscle dynamics cycle simulation curve of quadruped robot RAT is shown in Figure 14.Figure 14-(a) is kneed artificial-muscle length temporal evolution curve, Figure 14-(b) is kneed artificial-muscle contraction speed temporal evolution curve, Figure 14-(c) is that kneed artificial-muscle shrinks acceleration temporal evolution curve, and Figure 14-(d) is kneed power output temporal evolution curve.In one-period, recovery phase, joint angle changed greatly, and artificial-muscle length variations is larger, hip joint power output is in 80N, and knee joint power output is in 150N, and driving phase knee joint changes less, except there is output more energetically the moment of contacting to earth, power output little in other times.Simulation result shows, the application of linear electromagnetic array artificial-muscle aspect quadruped robot is feasible, because artificial-muscle does not move by gear train Direct Drive Robot, thereby it is high to have execution efficiency, the life-span is long, and redundancy is good, fast response time, the feature such as instantaneous acceleration is large.

Above-mentioned embodiment is used for explaining the present invention, does not limit the invention, and in the protection domain of spirit of the present invention and claim, any modification and change that the present invention is made, all fall into protection scope of the present invention.

Claims (4)

1. the method for designing of the netted array artificial-muscle of a kind skeletal muscle straight line, it is characterized in that: the method comprises a plurality of class half muscle segment drivers by the netted array artificial-muscle of class skeletal muscle straight line, a plurality of class half muscle segment drivers form class muscle fibril driver through series connection, the class muscle fibril driver of take is symcenter, other class muscle fibril drivers are arranged side by side and formed the netted symmetric array formula of hexagonal honeycomb structure, same layer class half muscle segment driver on each class muscle fibril driver aggregates into one by class sarolemma connector by all class muscle fibril drivers respectively, and at polymerization all-in-one-piece class muscle fibril driver two ends, be provided with class aponeurosis (aponeuroses) connector and form artificial-muscle, the columns m of the netted array artificial-muscle of such skeletal muscle straight line and number of plies n determine by following technical step:

(1) according to artificial-muscle application and applied environment, provide maximum target output displacement L _asmaxand artificial-muscle when motion the maximum target power output F that needs _asmax;

(2) calculate artificial-muscle parallel-connection and count layer by layer n, n is natural number, if the maximum output displacement of class half muscle segment driver is x _smax, have

$\frac{L_{\mathrm{as}\max }}{x_{s\max }}\&le;n<\frac{L_{\mathrm{as}\max }}{x_{s\max }}+1---\left(1\right)$

(3) calculate the minimum columns k of artificial-muscle series connection layer, k is natural number, if the minimum power output f of class half muscle segment driver _smin, have

$\frac{F_{\mathrm{as}\max }}{f_{s\min }}\&le;k<\frac{f_{\mathrm{as}\max }}{f_{s\min }}+1---\left(2\right)$

(4) calculate netted hexagonal number of total coils c (c is natural number) in artificial-muscle series connection layer, c need meet following formula

$1+6\&CenterDot;\underset{i=2}{\overset{c-1}{\mathrm{\&Sigma;}}}(i-2)\&le;k\&le;1+6\&CenterDot;\underset{i=2}{\overset{c}{\mathrm{\&Sigma;}}}(i-2)---\left(3\right)$

(5) finally determine that artificial-muscle array architecture is columns

m is natural number, the number of plies $n=\frac{L_{\mathrm{as}\max }}{x_{s\max }}.$

2. the method for designing of the netted array artificial-muscle of class skeletal muscle straight line as claimed in claim 1, it is characterized in that: the same layer class half muscle segment driver on each described class muscle fibril driver aggregates into one by class sarolemma connector by all class muscle fibril drivers respectively, and all kinds of sarolemma connectors are successively equidistant arranges side by side.

3. the method for designing of the netted array artificial-muscle of class skeletal muscle straight line as claimed in claim 1, is characterized in that: at polymerization all-in-one-piece class muscle fibril driver two ends, be provided with class aponeurosis (aponeuroses) connector, class aponeurosis (aponeuroses) connector is hexagonal structure.

4. the neural control method of class of the netted array artificial-muscle of class skeletal muscle straight line that claim 1 design obtains, is characterized in that: this control method comprises the steps:

The first step, in the control time Δ t resolving according to artificial-muscle upper strata controller, artificial-muscle target output displacement L _aswith and the target power output F in when motion _as;

Second step, advanced row artificial-muscle row are controlled, and calculate artificial-muscle parallel-connection key-course number of plies n, and n is natural number, if the maximum output displacement of class half muscle segment driver is x _smax, have

$\frac{L_{\mathrm{as}}}{x_{s\max }}\&le;n<\frac{L_{\mathrm{as}}}{x_{s\max }}+1---\left(4\right)$

The 3rd step, selects key-course according to power output minimum principle, and while moving according to artificial-muscle, the kinetics equation of class half muscle segment driver, judges and in its motion process, produce electromagnetic force f _{s (j)}, i.e. electromagnetic force f _{s (i) (j)}for all classes half muscle segment driver in shunt layer j produces monotonicity and the work shift x thereof of total electromagnetic force _sselect artificial-muscle key-course, if the electromagnetic force f that class half muscle segment driver produces _{s (j)}for Parallel Control, count layer by layer the increasing function of j, select work shift x _scan meet target output displacement L _as, and the shunt layer nearest apart from artificial-muscle starting point layer is key-course; Otherwise, if electromagnetic force f _{s (j)}during for the subtraction function of variable j, select work shift x _scan meet target output displacement L _as, and the shunt layer nearest apart from artificial-muscle stop layer is key-course;

The 4th step, in control time Δ t, in key-course, the output displacement of each class half muscle segment driver is artificial-muscle target output displacement L _as, the class half muscle segment driver in non-key-course is in self-locking state, no-output displacement;

The 5th step, carries out the capable control of artificial-muscle, the work shift x of real-time measure and control layer _s, determine the maximum power output f under this work shift _xmax(x _s);

$f_{\mathrm{xmsx}}\left(x_s\right)=f(x_s,I_{\max })=\frac{d{W}_m(x_s,I_{\mathrm{mas}})}{d{x}_s}=\frac{\&PartialD;}{\&PartialD;x_s}\left[{\&Integral;}_V{\&Integral;}_0^H(B\&CenterDot;\mathrm{dH})\mathrm{dV}\right]---\left(17\right)$

Wherein, I _maxfor the peak coil current of class half muscle segment driver, W _m(x _s, I _max) be magnetic field energy, x _sfor work shift, H is magnetic field intensity, and B is magnetic induction density, the integrating range that V is volume integral;

The 6th step, according to target power output F _asdetermine that artificial-muscle series connection layer activates number n _yneed to meet following formula:

f _xmax(x _s)·(n _y-1)≤F _as≤f _xmax(x _s)·n _y (18)

The 7th step, belongs to centrosymmetric image according to the reticulate texture of artificial-muscle, adopts to activate to activate according to centrosymmetric mode, and by the summation of all activated artificial-muscle series connection layer power output, be artificial-muscle target power output F _as, every pair of artificial-muscle series connection layer class power output Central Symmetry equates;

The 8th step, passes to controller by each the class half muscle segment driver resolving, and by the submissive control of R-C power displacement, completes power and the displacement output task of artificial-muscle in the instruction cycle.

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