CN105137761B - The adjustable feedback of electromagnetic force device of three-winding posture and its Attitude Calculation and current intelligent control method - Google Patents

The adjustable feedback of electromagnetic force device of three-winding posture and its Attitude Calculation and current intelligent control method Download PDF

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CN105137761B
CN105137761B CN201510628652.4A CN201510628652A CN105137761B CN 105137761 B CN105137761 B CN 105137761B CN 201510628652 A CN201510628652 A CN 201510628652A CN 105137761 B CN105137761 B CN 105137761B
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electric current
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袁志勇
童倩倩
朱炜煦
廖祥云
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Wuhan University WHU
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Abstract

The invention discloses a kind of adjustable feedback of electromagnetic force device of three-winding posture and coil Attitude Calculation and coil current intelligent control method, establish it is a kind of based on probability description to different spaces scope and the interactive application demand model of different electromagnetic force size and Orientations, and according to this demand model devise it is a kind of can be directed to distinct interaction application reduce power consumption coil computation method for attitude.Propose a kind of integrated current intelligent control method simultaneously, this method includes a coil current control interface driven based on ARM Cortex M3 embedded microcontrollers and H bridges, scope to feedback force and its required precision in a kind of application demand according to distinct interaction, one or more sampling resistors in parallel are sampled using current sensor, realize raising current sample precision and reduce the high-precision current Sampling techniques of power attenuation, and using on the basis of the technical limit spacing coil current, it is proposed that self-adaptive fuzzy PID algorithm carries out Intelligent adjustment to coil current.

Description

The adjustable feedback of electromagnetic force device of three-winding posture and its Attitude Calculation and current intelligent Control method
Technical field
The present invention relates to field of human-computer interaction, more particularly to the adjustable feedback of electromagnetic force device of three-winding posture and its posture Calculate and current intelligent control method.
Background technology
Berkelman et al. expands research to feedback of electromagnetic force technology the nineties in last century, but its design is set Standby very original, heavy, handle is constrained in framework, scope of activities very little [1] [2].Salcudean [3] and Brink [4] Et al. the method for sense of touch to simulating solid metope and frictional force by feedback of electromagnetic force studied, but Brink is only studied Monocoil situation, Salcudean have then made a very big equipment.
In recent years, the Liang Ge team where Berkelman and Hu has delivered the new results in feedback of electromagnetic force respectively. The Berkelman perfect electric current of magnet coil and the linear model of electromagnetic force, with the coefficient matrix of measuring coil in space Based on, stress model of the magnet in coil array has been drawn, small magnet is realized in magnet coil as theoretical foundation Suspension [5] [6] on array, and made a set of haptic feedback system [7] [8].Hu starts with from virtual operation, and slave unit is overall Angle describe a feedback of electromagnetic force system of virtual operation [9].However, Berkelman and Hu is not to magnet coil Posture provide tight explanation --- Berkelman simply puts coil into hexagonal honeycomb array, and Hu is simply straight See ground magnet coil is dispersedly placed in bowl-type region, and two have used far beyond the required electromagnetic wire number of turns per capita Amount.
And in fact, although the number of coils of redundancy can provide more more options when solving electric current, number of coils is got over Few, the solution and control to electric current are more convenient.Theoretically, three coils provide for the 3 D electromagnetic of a certain size and scope Magnetic field needed for force feedback.In addition, the posture of coil can have an impact to the electric current of solution, rational posture can make interaction The power consumption of coil is greatly reduced, otherwise interaction can be caused not reach actual demand or even can not complete.Therefore, find most Good coil posture is even more important.However, it is nonsensical to depart from interactive application demand only to talk optimum posture, how for handing over It is good problem to study that mutual application demand, which finds coil optimum posture,.
Bibliography
[1]Berkelman P J,Hollis R L,Salcudean S E.Interacting with virtual environments using a magnetic levitation haptic interface[C]//Intelligent Robots and Systems 95.′Human Robot Interaction and Cooperative Robots′, Proceedings.1995IEEE/RSJ International Conference on.IEEE,1995,1:117-122.
[2]Berkelman P J,Hollis R L,Baraff D.Interaction with a real time dynamic environment simulation using a magnetic levitation haptic interface device[C]//Robotics and Automation,1999.Proceedings.1999 IEEE International Conference on.IEEE,1999,4:3261-3266.
[3]Salcudean S E,Vlaar T D.On the emulation of stiff walls and static friction with a magnetically levitated input/output device[J].Journal of dynamic systems,measurement,and control,1997,119(1):127-132.
[4]Brink J B,Petruska A J,Johnson D E,et al.Factors affecting the design of untethered magnetic haptic interfaces[C]//Haptics Symposium (HAPTICS),2014IEEE.IEEE,2014:107-114.
[5]Berkelman P,Dzadovsky M.Magnet levitation and trajectory following motion control using a planar array of cylindrical coils[C]//ASME 2008 Dynamic Systems and Control Conference.American Society of Mechanical Engineers,2008:923-930.
[6]Berkelman P,Dzadovsky M.Magnetic levitation over large translation and rotation ranges in all directions[J].Mechatronics,IEEE/ASME Transactions on,2013,18(1):44-52.
[7]Peter Berkelman,Sebastian Bozlee,and Muneaki Miyasaka.Interactive rigid-body dynamics and deformable surface simulations with co-located maglev haptic and 3d graphic display.International Journal On Advances in Intelligent Systems,6(3 and 4):289–299,2013.
[8]Peter Berkelman,Sebastian Bozlee,and Muneaki Miyasaka.Interactive dynamic simulations with co-located maglev haptic and 3d graphic display.In ACHI2013,The Sixth International Conference on Advances in Computer-Human Interactions,pages 324–329,2013.
[9]Hu J.Magnetic haptic feedback systems and methods for virtual reality environments:U.S.Patent Application 11/141,828[P].2005-6-1.
The content of the invention
For conventional feedback of electromagnetic force equipment coil placing attitude it is not rigorous the problem of, invention introduces coil position pendulum The concept related to interactive application demand is put, establishes model of the description interactive application to electromagnetic field demand, and give basis The method that interactive application demand calculates coil posture.In addition, the present invention proposed for feedback of electromagnetic force device it is a kind of high-precision Coil current intelligent control method.
The present invention adopts the following technical scheme that realization：
A kind of adjustable feedback of electromagnetic force device of three-winding posture, including the sliding support 2,3 of base 1, three coil hold 3,3 coils 4 of device and coil driver 12；Slide rail is provided with base 1, sliding support 2 is arranged on slide rail, and coil holds Device 3 is arranged on sliding support 2, and coil 4 is fixed on coil container 3, and coil driver 12 is connected with coil 4；Three lines Circle can freely be adjusted in plane parallel with slide rail, perpendicular to the ground, by the direction and position of regulating winding, be adapted to different Spatial dimension and the interactive application demand of different electromagnetic force size and Orientations are (i.e.：Device space adjustable extent be 300mm × 300mm × 300mm, feedback force magnitude range are 0-4N).
The computational methods of the adjustable coil posture include herein below：
(2a) introduces probability cloud description adaptation different spaces scope and the interactive application of different electromagnetic force size and Orientations and needed The amount asked, the amount Q for being defined on t are：
Q (t)=(L (t), B (t))
Wherein, L (t) and B (t) represents that t needs to produce magnetic field B (t), and L (t), B (t) in position L (t) respectively It is the trivector on t；
The joint probability density that each point occurs in the sextuple space where probability cloud f (L, B) is Q (t) is defined, to any Position and magnetic field L0,B0, its calculation formula is：
Wherein, L0x,L0y,L0z,B0x,B0y,B0zRespectively L0,B0Component in the dimension of three, space,G(L0,B0) it is the regional ensemble for meeting following condition in time range t ∈ [0, T]：
Lx(t)≤L0x∩Ly(t)≤L0y∩Lz(t)≤L0z∩Bx(t)≤B0x∩By(t)≤B0y∩Bz(t)≤B0z
Wherein, symbol ∩ represent and.
m(G(L0,B0)) estimating for set G, Measure representation set G size, i.e., the institute in time range t ∈ [0, T] The time span accounted for；
(2b) is directed to the magnet coil optimum posture computation model of electromagnetic force interactive application demand,
Define optimizing evaluation function E：
Wherein, A (L) is coefficient matrix of three coils at the L of position, and d (L, B) is L, the integration infinitesimal in B spaces.
In the parameter space of coil posture, optimizing is carried out using optimizing evaluation function pair E, finds the optimal appearance of coil State.
Described coil driver 12 is used for the intelligent control of coil current, and the drive circuit 12 includes embedded micro-control Device processed, power module, H bridges drive module, current sample module, intelligent PID current regulating module, communication module, magnet coil Overheat protector module, power power-supply over-and under-voltage overcurrent protection module, abnormal alarm module etc..Wherein, embedded microcontroller Using ARM Cortex-M3 as kernel control chip.The annexation of above-mentioned intermodule is：Embedded microcontroller ARM Pwm signal caused by Cortex-M3 produces electric current through H bridges drive module driving electromagnetic coil array, to realize that electric current is accurately controlled System, is sampled using current sample module to the electric current in coil, and sampled signal is converted into digital PWM signal, finally Real-time closed-loop regulation is carried out to the electric current in coil by intelligent PID module.
A kind of coil current intelligent control method based on said apparatus, including herein below：
First, ARM Cortex-M3 embedded microcontrollers produce the pwm signal corresponding with required electric current, the signal By driving NMOSFET pipes through H bridges driving chip after current limliting, signal isolation protection circuit, so as to obtain electric current in coil, use Current sample module pair is sampled with the sampling resistor that coil is in series, and sampled signal is converted into digital PWM signal, is entered And the actual current in magnet coil is calculated, real-time closed-loop tune is carried out to the electric current in coil finally by intelligent PID module Section, to realize that the accurate feedback of electric current controls, specifically include following steps：
Step 1：According to the dutycycle for calculating gained electric current ARM Cortex-M3 embedded microcontroller control pwm signals；
Step 2：Above-mentioned pwm signal after current limliting, light-coupled isolation protection circuit by passing through by two panels H bridges driving chip and 4 The H bridges that NMOSFET pipes are formed drive magnet coil, and electric current is produced in coil；
Step 3：The voltage signal at sampling resistor both ends is detected using high-voltage current sensor and is converted into numeral PWM；
Step 4：The actual current passed through in magnet coil is calculated according to the PWM obtained in step 3 dutycycle；
Step 5：The increment of electric current in magnet coil is calculated using self-adaptive fuzzy PID algorithm, goes to step 1；
The above method is unicoil current control method, for the adjustable device for force feedback of three-winding posture, using two panels ARM Cortex-M3 embedded microcontrollers three coils of chip controls, each embedded microcontroller at most two electricity of control Magnetic coil.
In the step 2, the driving of H bridges uses complementary PWM type of drive, the H bridge driving chips produced from IR companies, its In a driving chip realize the driving of half-bridge, realize that full-bridge drives using two driving chips, half-bridge includes two NMOSFET Pipe and two fly-wheel diodes.The pwm signal of ARM Cortex-M3 outputs is by optic coupling element to ensure embedded microcontroller Can normal work, then the two-way pwm signal input for driving half-bridge is used for chip with door function, its output signal Two NMOSFET pipes for preventing from being controlled by same driving chip simultaneously turn on, by power supply bootstrap module and after filtering, The protection of NMOSFET tube grids, H bridge spikes ripples such as absorb at optimization and the safeguard measure, realize NMOSFET conductings and cut-off state Control, so as to realize the control of forward and reverse electric current in magnet coil so that the operation pair in magnetic field caused by electromagnetic coil array As experiencing repulsive force or attraction.In addition, dead time is set to protect NMOSFET pipes and power supply.
In the step 3,4, the sampling resistor being series in electromagnetic coil circuit is carried out by high-voltage current sensor Detection, the number of above-mentioned sampling resistor is n, n >=1, is that n identical sampling resistor is in parallel if n >=2, high-tension electricity spreads Sensor samples to the voltage at the sampling resistor both ends after parallel connection, and the dutycycle of the pwm signal of current sensor output is entered Row measures and then calculates detection current value, it is assumed that it is I to detect gained electric current by current sensor0, then each sampling resistor is passed through Electric current be I1=I2=...=In=I0；
Therefore, it is I by the actual current of magnet coil：
I=I1+I2+…+In=nI0
Wherein, n size determines according to the requirement in practical application to the scope and force feedback precision of force feedback.
In the step 5, using self-adaptive fuzzy PID algorithm, the magnet coil obtained to described current sample module In actual current carry out closed-loop control so that electric current in coil with by the electric current that feedback force calculates in interactive application demand In error range；
Control for electric current in feedback of electromagnetic force device, the difference equation of pid number controller are：
Wherein, u (k) is the electric current in the k moment magnet coils as obtained by regulation；E (k) for calculate gained electric current r (k) with Sample rate current c (k) error signal, i.e. e (k)=r (k)-c (k), make ec(k) error change for being current error signal e (k) Rate；Kp、Ki、KdRespectively PID ratios, integration and differential coefficient, make Δ kp、Δki、ΔkdParameter K during respectively adjustingp、 Ki、KdCorrection；Self-adaptive fuzzy algorithm is used to determine above-mentioned 3 parameter Kp、Ki、Kd；
Self-adaptive fuzzy PID algorithm realizes comprising the following steps that for solenoid current intelligent control：
Step 1：Choose the current error signal e and its error rate e of magnet coilcFor the input of fuzzy controller, Output quantity is the correction amount k of pid parameterp、Δki、Δkd；
Step 2：By the error originated from input e of fuzzy controller, its error rate ecWith the output Δ k of fuzzy controllerp、Δ ki、ΔkdIt is blurred, is respectively converted into linguistic variable E, Ec、ΔKp、ΔKi、ΔKd, choose membership function；
Step 3：Suitable fuzzy reasoning table is established, obtains solenoid current pid control parameter correction amount Kp、ΔKi、 ΔKdFuzzy reasoning table；
Step 4：The fuzzy reasoning table established according to step 3, to fuzzy input variable E, E of systemcFuzzy reasoning solves Fuzzy relation equation, obtain the fuzzy output amount of system；
Step 5：The fuzzy output amount of step 4 is converted to by accurate output quantity by defuzzification method, then by it through chi Degree conversion obtains reality output amount Δ kp、Δki、Δkd；
Step 6：The increment of electric current in magnet coil is calculated, and the pwm signal of ARM Cortex-M3 outputs is adjusted Section, goes to step 1；
Above-mentioned self-adaptive fuzzy PID algorithm program is run in ARM Cortex-M3 embedded microcontrollers.
Compared with prior art, the present invention has following innovation and advantage：
1. the adjustable feedback of electromagnetic force device of three-winding posture, the direction and position of its coil can answer according to distinct interaction It is adjusted with demand, there is scalability.
2. introducing probability cloud to describe the demand of electromagnetic force interaction, the coil for interactive application demand can be calculated Optimum posture so that the power consumption of interactive device is relatively low.
3. by producing bidirectional current in H bridge type of drive magnet coils, the electric current is enabled in its generation Magnetic field in object experience with truth identical feedback force, control efficiently, it is accurate.
4. realize the sampling of electric current in magnet coil by the way of n sampling resistor is in parallel, sampling resistor it is individual several The demand of force feedback scope and precision is determined according to practical application, can meet to be actually needed and there is flexibility.
5. under ARM Cortex-M3 embedded microcontrollers, using self-adaptive fuzzy PID algorithm in magnet coil Electric current is controlled, and is had the advantages that reliability height, strong antijamming capability, control accuracy are high, can effectively and precisely be realized power Feedback.
Brief description of the drawings
Fig. 1 is the adjustable feedback of electromagnetic force device of three-winding posture；
Fig. 2 is base effects figure and its three-view diagram；
Fig. 3 is sliding support design sketch and its three-view diagram；
Fig. 4 is coil container design sketch and its three-view diagram；
Fig. 5 is formed for feedback of electromagnetic force device current intelligent control system；
Fig. 6 is that the hardware circuit of H bridge driving coil electric currents is formed；
Fig. 7 is solenoid current driving principle figure；
Fig. 8 is adaptive Fuzzy PID Control system block diagram；
Fig. 9 is self-adaptive fuzzy PID algorithm implementation process；
Wherein, 1-base 1,2-sliding support, 3-coil container, 4-coil, 5-lock screw hole, 6-rotary shaft Hole, 7-fan annular lock track, 8-rotational axis hole two, 9-lock hole, 10-screw hole, 11-opening, 12-coil drive Circuit, 13-slide rail.
Embodiment
In order to make it easy to understand, below in conjunction with the accompanying drawings and example, the embodiment of the present invention is made further detailed Explanation.Following examples are merely to illustrate the present invention, but are not intended to limit the scope of the present invention.
1. the adjustable feedback of electromagnetic force device of three-winding posture
One three-winding feedback of electromagnetic force device, the posture (direction and position) of its coil is adjustable, i.e. direction and position can Adjust, to adapt to the interactive application demand of different spaces scope and different electromagnetic force size and Orientations.See Fig. 1, it is provided by the invention Three-winding feedback of electromagnetic force device includes base 1 (referring to Fig. 2), three sliding supports 2 (referring to Fig. 3), 3 coil containers 3 (in detail See Fig. 4), 3 coils 4 and coil driver 12.
Base such as Fig. 2, possess three centered on base center point, opened with 120 degree of angles, the cunning being distributed in divergent shape Rail 13, for providing track to sliding support.Sliding support such as Fig. 3, its bottom possess groove to be slided on the track of base, And possess lock screw hole 5 and secured a bracket to when sliding into optimum position (being calculated using the algorithm described in claim 6) On track.Its upper side has rotational axis hole 1 and fan annular lock track 7 so that coil container can be in sliding support upper measurement Rotate around rotational axis hole and locked by fanning annular lock track.There is rotational axis hole 28 coil container such as Fig. 4, side, Pass through screw connection with the rotational axis hole of sliding support so that coil container can turn in sliding support upper measurement around rotational axis hole It is dynamic.Side rotational axis hole nearby has lock hole 9 so that when rotating, the screw through lock hole can be in the fan of sliding support Slided in annular lock track, and screw is tightened when turning to optimum position (being calculated using the algorithm described in claim 6) Locking.Its bottom possesses the screw hole 10 of fixed coil and is easy to the opening 11 of coil copper cash cabling.Coil electricity produces electricity Magnetic force, bottom possess screw hole, are fixed with coil container.Coil driver 12 is used to control the electric current in magnet coil big Small, its specific implementation is described in detail in 3-7 points.
2. the Attitude Calculation of coil is carried out for interactive application demand
2a. introduces probability cloud description adaptation different spaces scope and the interactive application of different electromagnetic force size and Orientations and needed Ask；
In feedback of electromagnetic force interaction, feedback of electromagnetic force device needs specific big in ad-hoc location generation at certain moment The small and magnetic field in direction.Wherein position is represented by the vector in three dimensions with magnetic field.Therefore in a period of time T, interaction During the amount of application demand be represented by the function of position and magnetic field on the time, i.e.,：
Q (t)=(L (t), B (t))
Wherein, L (t) and B (t) represents that t needs to produce magnetic field B (t), and L (t), B (t) in position L (t) respectively It is the trivector on t, is represented by
Q (t)=(Lx(t),Ly(t),Lz(t),Bx(t),By(t),Bz(t))
Wherein, t ∈ [0, T].
The joint distribution function of interactive application demand is made as F (L, B) (or F (Lx,Ly,Lz,Bx,By,Bz)), to optional position With magnetic field L0,B0, define F (L0,B0) be
Wherein, G (L0,B0) it is the regional ensemble for meeting following condition in time range t ∈ [0, T]：
Lx(t)≤L0x∩Ly(t)≤L0y∩Lz(t)≤L0z∩Bx(t)≤B0x∩By(t)≤B0y∩Bz(t)≤B0z
m(G(L0,B0)) estimating for set G.
The joint probability density function for making interactive application demand is f (L, B), to optional position and magnetic field L0,B0, define f (L0,B0) be
In practical engineering application, interaction is generally represented with discrete form, the interactive application represented discretization Demand is
Wherein, N is that sequential element is total, M (L0,B0) it is (L in sequence0,B0) occur number.
Joint probability density function f (L, B) on sextuple space, describe specific in ad-hoc location generation in interaction Probability cloud in the probability in magnetic field, referred to herein as sextuple space, application demand may be defined as joint probability in interaction The probability cloud that density function f (L, B) is represented.
2b. is directed to the magnet coil optimum posture computation model of electromagnetic force interactive application demand；
For certain interactive application demand, the optimum posture of the probability cloud computing coil in 2a can be passed through.
It is the power for completing the consumption of interaction coil to define optimizing evaluation function E：
Wherein, A (L) is coefficient matrix of three coils of explanation in document [6] at the L of position, and d (L, B) is L, B spaces In integration infinitesimal.
By the foregoing present apparatus structure is formed to understand, the attitude parameters of three coils includes placed angle α, beta, gamma and With the distance l of central pointA,lB,lC.If three coils are symmetrically put, have：
L=lA=lB=lC
In two-dimensional spaceIn find E minimum value so that E is minimumThe as optimum posture of coil.
During specific implementation, coil Attitude Calculation arthmetic statement is as follows：
Above-mentioned algorithm by taking Optimum search as an example, but is not limited to such a optimized algorithm when being related to function E optimizing, Other optimized algorithms are all applied to the optimization process, belong in the scope of this patent.
3. the realization of the coil current intelligent control of the adjustable feedback of electromagnetic force device of three-winding posture
See Fig. 5, coil driver is used for the control of solenoid current, mainly including following module：Embedded micro-control Device processed, power module, H bridges drive module, current sample module, intelligent PID current regulating module, communication module, magnet coil Overheat protector module, power power-supply over-and under-voltage overcurrent protection module, abnormal alarm module etc..Power module provides for each module Power supply, embedded microcontroller is as kernel control chip, the generation pwm signal corresponding with electric current needed for force feedback, the letter Number by H bridges drive module control electromagnetic coil array in electric current, for improve control accuracy, using current sample module to line Actual current in circle is sampled, and sampled signal is changed by signal and produces digital PWM, and the pwm signal is through adaptive fuzzy PID adjusts the finally accurate control to electric current.
This example using ARM Cortex-M3 series embedded microcontroller AT91SAM3U4E as kernel control chip, The control of electric current in magnet coil is realized by the dutycycle of its control pwm signal.There is provided in this example by Switching Power Supply 24V voltages are supplying current thereto, and H bridge driving chip IR2110 and solenoid current sampling A/D chip IR2175 need 15V and 5V power supplys, kernel control chip AT91SAM3U4E need 3.3V power supplys, and wherein 15V, 5V power supply are by 24V Switching Power Supplies Obtained by DC-DC voltage conversion chips TPS5430, and then 5V power supplys are converted to 3.3V power supplys through electric pressure converter.Using every By data signal separated from power module with analog signal, this example selection B050xS power isolation modules, to improve essence Degree, isolating for data signal and analog signal is realized using B0505S power modules first, then the 5V power supplys after isolation are passed through Voltage conversion chip AMS1117-3.3 is converted to 3.3V.
For the operation object under a certain motion state, it is necessary to which the feedback force in a certain size and direction, AT91SAM3U4E are embedding The intelligent control detailed process for entering the formula microcontroller implementation electric current corresponding with above-mentioned feedback force is as follows：
Step 1：According to the dutycycle for calculating gained electric current AT91SAM3U4E control pwm signals；
Step 2：Above-mentioned pwm signal after the protection circuits such as a series of current limliting, light-coupled isolation by passing through by two panels IR2110 And the H bridges that 4 NMOSFET pipes are formed drive magnet coil, and electric current is produced in coil；
Step 3：The voltage signal at sampling resistor both ends is detected using high-voltage current sensor IR2175 and is converted into Digital PWM；
Step 4：The actual current passed through in magnet coil is calculated according to the PWM obtained in step 3 dutycycle；
Step 5：The increment of electric current in magnet coil is calculated using self-adaptive fuzzy PID algorithm, goes to step 1.
Described above is unicoil current control.For the adjustable device for force feedback of three-winding posture, this example uses two Piece AT91SAM3U4E embedded microcontrollers three coils of chip controls, each embedded microcontroller are at most controllable two Magnet coil.
4.H bridge drive modules
The hardware circuit master-plan of 4a.H bridge driving coil electric currents
More traditional PWM type of drive, the follow current of the H bridges of complementary PWM driving are managed or two from two high-pressure side NMOSFET Individual low-pressure side NMOSFET pipes are flowed back, and two recirculation loops are present, can be avoided for a long time in same side reflux, therefore the present invention adopts With complementary PWM type of drive.
See Fig. 6, this example H bridges driving chip selects the IR2110 of IR companies production, full-bridge is realized using two panels IR2110 Driving.The pwm signal of AT91SAM3U4E outputs is first by optocoupler HCPL-2631 to ensure core controller AT91SAM3U4E being capable of normal work.For half-bridge, two-way pwm signal inputs 2 input signals of 4 tunnel independences to lose-lose Enter with door chip SN74C00, if two-way pwm signal is high level, SN74HC00 outputs are high level, this high level signal Two input channels can be blocked by inputting to driving chip IR2110, to realize the protection to NMOSFET pipes.In addition, design IR2110 high-pressure sides boostrap circuit realizes the normally of high-pressure side NMOSFET pipes, is born to reduce IR2110 chip Vs pins Punching, in each NMOSFET source electrode and a drain electrode Schottky diode in parallel.
4b.H bridges drive module controls the specific implementation of solenoid current
To meet the needs in numerous interactive application fields, feedback of electromagnetic force device can be produced with repulsion and sucking action Feedback force.Therefore, bidirectional current should can be produced in magnet coil.
See Fig. 7, AT91SAM3U4E exports two groups of reverse pwm signals of certain dutycycle, to two groups of H bridges both sides NMOSFET pipes control respectively, and Q1 and Q2 are one group, and alternate conduction, same Q3 and Q4 are one group of alternate conduction.If Q1 and Q4 are simultaneously Conducting, magnet coil ends A and B apply forward voltage, and Q2 and Q3 conductings, magnet coil both ends apply backward voltage, Q1 and Q3 Simultaneously turn on magnet coil when being simultaneously turned on Q2 and Q4 and be in loop discharge regime caused by self-induction.Adjust two groups of pwm signals Dutycycle be average current direction and size of current in controllable magnet coil.To avoid high and low pressure side NMOSFET pipes same When turn on, set suitable dead time with protect NMOSFET manage and power supply.Dead time setting is too small, may cause height Press the NMOSFET pipes synchronization of side to turn on and cause power supply shorted to earth；And dead time sets long, high and low pressure side NMOSFET is in cut-off state, and the follow current of magnet coil can cause occur very big ripple or impact in H-bridge circuit Signal.Dead time typically sets scope preferable for 500nS~1 μ S effects.
5. the method for sampling of magnet coil actual current
The present invention is the electric current using H bridge drive control magnet coils, due to the shadow of the factors such as external environment, electromagnetic interference Ring, the actual current in final magnet coil by the current value of feedback force calculating with having certain deviation.Therefore, it is necessary to electromagnetism Coil current is sampled, to realize the purpose accurately controlled.
The individual sampling resistor both ends in parallel of n (n >=1) that this example is connected using the IR2175 detections of IR companies with magnet coil Voltage, and be pwm signal by current value linear transformation, AT91SAM3U4E measures the dutycycle of the signal by timer, and The electric current of magnet coil is calculated according to correlation formula.
Above-mentioned n sampling resistor is identical.Control of the selection of sampling resistor to electric current in magnet coil is most important, Sampling resistor is excessive, and not only collectable current range is too small, and power attenuation on sampling resistor can be made bigger, resistance hair Heat can influence the non-linear of its precision and temperature rise coefficient；Sampling resistor is smaller, although the ability in sampling of sample circuit can be improved, But it can make it that output voltage is smaller on sampling resistor, so as to cause application condition big, reduce sampling precision.It is however, identical by n Resistor coupled in parallel, can both use slightly larger sampling resistor, improve sampling precision, enable to the electricity on each sampling resistor again Stream is smaller, subtracts low power loss, so as to ensure sampling resistor normal work.
The number n of sampling resistor is depending on difference of the different application to force feedback required precision in the present invention.For example, If the feedback of electromagnetic force dress of the invention is applied to require feedback force in higher virtual operation, need anti-according to power The precision of the accuracy computation phase induced current of feedback, the scope of electric current is gone out according to the range computation of force feedback, with reference to electric current precision with Scope determines n size.
Being calculated in the higher application of feedback force precision needs n sampling resistor to realize current sample, if current sense Device detection gained electric current is I0, then it is by the electric current of each sampling resistor：
I1=I2=...=In=I0
Therefore, it is I by the actual current of magnet coil：
I=I1+I2+…+In=nI0
6. Adaptive Fuzzy PID realizes that coil current accurately controls
The purpose sampled to the electric current in magnet coil is by the realization pair of the deviation of sample rate current and actual current The accurate control of electric current, the present invention propose to use self-adaptive fuzzy PID algorithm.The differential equation mathematics model of pid algorithm is：
Wherein, u (t) is the output control amount of PID control；KpFor proportionality coefficient；TiFor integration time constant；TdFor differential Time constant；E (t) is error signal.The difference equation of pid number controller can be obtained by discretization.It is T to make the sampling period, The integral coefficient that PID can then be obtained isDifferential coefficient is
The difference equation of pid number controller is in feedback of electromagnetic force device current control system：
Wherein, u (k) is the electric current in the k moment magnet coils as obtained by regulation；E (k) for calculate gained electric current r (k) with Sampling gained electric current c (k) error signal, i.e. e (k)=r (k)-c (k), make ec(k) error for being current error signal e (k) Rate of change；Kp、Ki、KdRespectively PID ratios, integration and differential coefficient, make Δ kp、Δki、ΔkdParameter is regulation process respectively Middle Kp、Ki、KdCorrection.Self-adaptive fuzzy algorithm is used to determine Kp、Ki、Kd.Adaptive Fuzzy PID Control system block diagram is shown in Fig. 8, first by the error e of electric current, error change needed for the actual current and feedback of electromagnetic force of magnet coil obtained by current sample Rate ecAnd output quantity blurring, K is gone out by fuzzy rule and reasoning and calculationp、Ki、Kd, obtained above-mentioned 3 parameters are used for PID regulating calculations go out current increment, eventually for the regulation of pwm signal.
See Fig. 9, self-adaptive fuzzy PID algorithm realizes comprising the following steps that for solenoid current intelligent control：
Step 1：Choose the current error signal e and its error rate e of magnet coilcFor the input of fuzzy controller, Output quantity is the correction amount k of pid parameterp、Δki、Δkd, e and e is calculated according to current detecting resultc；
Step 2：By error e, error rate ecWith the output Δ k of fuzzy controllerp、Δki、ΔkdCarry out at blurring Reason, above-mentioned variable are respectively converted into linguistic variable E, E by change of scalec、ΔKp、ΔKi、ΔKd, and select person in servitude to be subordinate to triangle Spend function；
Step 3：By inquiring about the fuzzy reasoning table established according to actual interactive application demand, solenoid current control is calculated System pid control parameter correction amount K processedp、ΔKi、ΔKd；
Step 4：By defuzzification method (such as weighted mean method) by the fuzzy defeated of solenoid current control system Output is converted to accurate output quantity, then it is obtained into actual output quantity Δ k through change of scalep、Δki、Δkd；
Step 5：Calculate pid parameter Kp、Ki、Kd, and pass through the electric current of PID controller calculating magnet coil；
Step 6：If the electric current that step 5 calculates goes to step 7, otherwise it is modified, after amendment not less than its threshold value Turn；
Step 7：PWM controlled quentity controlled variables are calculated, and 1 is gone to step to error signal and error rate assignment again.

Claims (8)

  1. A kind of 1. adjustable feedback of electromagnetic force device of three-winding posture, it is characterised in that：Including base (1), three sliding supports (2), 3 coil containers (3), 3 coils (4) and coil driver (12)；Slide rail is provided with base (1), slides branch Frame (2) is arranged on slide rail, and coil container (3) is arranged on sliding support (2), and coil (4) is fixed on coil container (3), Coil driver (12) is connected with coil (4)；Three coils can freely be adjusted in plane parallel with slide rail, perpendicular to the ground Section, by the direction and position of regulating winding, adapt to different spaces scope and the interactive application of different electromagnetic force size and Orientations Demand；Sliding support bottom possesses groove to be slided on the track of base, and possesses lock screw hole (5) and sliding into most preferably Secured a bracket to during position on track；Sliding support (2) upper side has rotational axis hole one (6) and fan annular lock track (7) so that coil container can be rotated around rotational axis hole in sliding support upper measurement and locked by fanning annular lock track； There is rotational axis hole two (8) coil container side, passes through screw connection with the rotational axis hole one (6) of sliding support so that coil holds Device can rotate in sliding support upper measurement around rotational axis hole two (8)；Rotational axis hole two (8) nearby has lock hole (9) so that is turning When dynamic, the screw through lock hole can slide in the fan annular lock track of sliding support, and turn to optimum position When tighten screw locking；Sliding support (2) bottom possesses the screw hole (10) of fixed coil and is easy to coil copper cash cabling It is open (11)；Coil electricity produces electromagnetic force, and bottom possesses screw hole, fixed with coil container.
  2. 2. the adjustable feedback of electromagnetic force device of three-winding posture according to claim 1, it is characterised in that：Described coil Drive circuit (12) is used for the intelligent control of coil current, and coil driver (12) includes embedded microcontroller, power supply mould Block, H bridges drive module, current sample module, intelligent PID current regulating module, communication module, magnet coil overheat protector mould Block, power power-supply over-and under-voltage overcurrent protection module, abnormal alarm module；Wherein, embedded microcontroller uses ARM Cortex-M3 is as kernel control chip；The annexation of above-mentioned intermodule is：Embedded microcontroller ARM Cortex-M3 Caused pwm signal produces electric current through H bridges drive module driving electromagnetic coil array, to realize that electric current accurately controls, using electricity Stream sampling module is sampled to the electric current in coil, and sampled signal is converted into digital PWM signal, finally by intelligence PID current regulating modules carry out real-time closed-loop regulation to the electric current in coil.
  3. A kind of 3. adjustable feedback of electromagnetic force device of three-winding posture according to claim 2, it is characterised in that：Described H bridges drive module uses complementary PWM type of drive, and a driving chip realizes the driving of half-bridge, using two driving chip realities Existing full-bridge driving, half-bridge include two NMOSFET pipes and two fly-wheel diodes；The PWM letters of the outputs of ARM Cortex-M3 first Number by optic coupling element with ensure embedded microcontroller can normal work, then by drive half-bridge two-way pwm signal it is defeated Enter there is the chip with door function, its output signal is used to prevent two NMOSFET controlled by same driving chip to manage simultaneously Conducting, by power supply bootstrap module and after filtering, the protection of NMOSFET tube grids, the optimization and protection of the absorption of H bridge spikes ripple Measure, NMOSFET conductings and the control of cut-off state are realized, so as to realize the control of electric current in magnet coil.
  4. A kind of 4. coil appearance of the adjustable feedback of electromagnetic force device of three-winding posture based on the claims 1-3 any one State computational methods, it is characterised in that including herein below：
    (2a) introduces the description of probability cloud and adapts to different spaces scope and the interactive application demand of different electromagnetic force size and Orientations Amount, the amount Q for being defined on t are：
    Q (t)=(L (t), B (t))
    Wherein, L (t) represents interactive application in the location of t L (t), and B (t) represents interactive application t in position L (t) need to produce magnetic field B (t), and L (t), B (t) are the trivector on t；
    The joint probability density that each point occurs in the sextuple space where probability cloud f (L, B) is Q (t) is defined, to optional position L0With magnetic field B0, its calculation formula is：
    <mrow> <mi>f</mi> <mrow> <mo>(</mo> <msub> <mi>L</mi> <mn>0</mn> </msub> <mo>,</mo> <msub> <mi>B</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <msup> <mo>&amp;part;</mo> <mn>6</mn> </msup> <mi>F</mi> <mrow> <mo>(</mo> <msub> <mi>L</mi> <mn>0</mn> </msub> <mo>,</mo> <msub> <mi>B</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> </mrow> <mrow> <mo>&amp;part;</mo> <msub> <mi>L</mi> <mrow> <mn>0</mn> <mi>x</mi> </mrow> </msub> <mo>&amp;part;</mo> <msub> <mi>L</mi> <mrow> <mn>0</mn> <mi>y</mi> </mrow> </msub> <mo>&amp;part;</mo> <msub> <mi>L</mi> <mrow> <mn>0</mn> <mi>z</mi> </mrow> </msub> <mo>&amp;part;</mo> <msub> <mi>B</mi> <mrow> <mn>0</mn> <mi>x</mi> </mrow> </msub> <mo>&amp;part;</mo> <msub> <mi>B</mi> <mrow> <mn>0</mn> <mi>y</mi> </mrow> </msub> <mo>&amp;part;</mo> <msub> <mi>B</mi> <mrow> <mn>0</mn> <mi>z</mi> </mrow> </msub> </mrow> </mfrac> </mrow>
    Wherein, L0x,L0y,L0z,B0x,B0y,B0zRespectively L0,B0Component in the dimension of three, space,G(L0,B0) it is the regional ensemble for meeting following condition in time range t ∈ [0, T]：
    Lx(t)≤L0x∩Ly(t)≤L0y∩Lz(t)≤L0z∩Bx(t)≤B0x∩By(t)≤B0y∩Bz(t)≤B0z
    Wherein, symbol ∩ represent and；Lx(t),Ly(t),Lz(t),Bx(t),By(t),Bz(t) it is respectively L (t), B (t) is in sky Between component in three dimensions；
    m(G(L0,B0)) estimating for set G, Measure representation set G size, i.e., shared by time range t ∈ [0, T] Time span；Wherein T refers to the total time of an interaction consumption；
    (2b) is directed to the magnet coil optimum posture computation model of electromagnetic force interactive application demand,
    Define optimizing evaluation function E：
    <mrow> <mi>E</mi> <mo>=</mo> <munder> <mrow> <mo>&amp;Integral;</mo> <mo>&amp;Integral;</mo> </mrow> <mrow> <mi>L</mi> <mo>,</mo> <mi>B</mi> </mrow> </munder> <mi>f</mi> <mrow> <mo>(</mo> <mi>L</mi> <mo>,</mo> <mi>B</mi> <mo>)</mo> </mrow> <msup> <mi>B</mi> <mi>T</mi> </msup> <msup> <mi>A</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msup> <msup> <mrow> <mo>(</mo> <mi>L</mi> <mo>)</mo> </mrow> <mi>T</mi> </msup> <msup> <mi>A</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mrow> <mo>(</mo> <mi>L</mi> <mo>)</mo> </mrow> <mi>B</mi> <mi>d</mi> <mrow> <mo>(</mo> <mi>L</mi> <mo>,</mo> <mi>B</mi> <mo>)</mo> </mrow> </mrow>
    Wherein, subscript " -1 " represents that to matrix inversion A (L) is coefficient matrix of three coils at the L of position, and d (L, B) is L, B Integration infinitesimal in space；
    In the parameter space of coil posture, optimizing is carried out using optimizing evaluation function pair E, finds the optimum posture of coil.
  5. 5. a kind of coil current based on the adjustable feedback of electromagnetic force device of three-winding posture as claimed in claim 3 is intelligently controlled Method processed, it is characterised in that including herein below：
    First, ARM Cortex-M3 embedded microcontrollers produce the pwm signal corresponding with required electric current, and the signal is through H bridges Driving chip driving NMOSFET pipes, so as to obtain electric current, the sampling resistor that current sample module pair is in series with coil in coil Sampled, and sampled signal is converted into digital PWM signal, and then calculate the actual current in magnet coil, finally led to Cross intelligent PID current regulating module and real-time closed-loop regulation is carried out to the electric current in coil, to realize that the accurate feedback of electric current controls, Specifically include following steps：
    Step 1：According to the dutycycle for calculating gained electric current ARM Cortex-M3 embedded microcontroller control pwm signals；
    Step 2：Above-mentioned pwm signal after current limliting, light-coupled isolation protection circuit by passing through by two panels H bridges driving chip and 4 The H bridges that NMOSFET pipes are formed drive magnet coil, and electric current is produced in coil；
    Step 3：Current sample module is sampled to sampling resistor using high-voltage current sensor and is turned ohmically pressure drop It is changed to digital PWM；
    Step 4：The actual current passed through in magnet coil is calculated according to the PWM obtained in step 3 dutycycle；
    Step 5：The increment of electric current in magnet coil is calculated using self-adaptive fuzzy PID algorithm, goes to step 1；
    The above method is unicoil current control method, for the adjustable device for force feedback of three-winding posture, using two panels ARM Three coils of Cortex-M3 embedded microcontrollers chip controls, each embedded microcontroller at most can control two electromagnetism Coil.
  6. 6. coil current intelligent control method according to claim 5, it is characterised in that：In the step 2, to meet not With the demand in interactive application field, feedback of electromagnetic force device needs to produce the feedback force with repelling with sucking action, accordingly Need to produce bidirectional current in magnet coil, ARM Cortex-M3 export the pwm signal corresponding with required feedback force, use it The NMOSFET pipes of H bridges are controlled, the size of PWM duty cycle determines that magnet coil both ends average voltage is just or negative, in coil Average current is positive or reverse, so as to determine that the operation object being in magnetic field caused by electromagnetic coil array experiences row Repulsion or attraction；In addition, suitable dead time is set to protect NMOSFET pipes and power supply.
  7. 7. coil current intelligent control method according to claim 6, it is characterised in that：In the step 3,4, electric current is adopted Egf block is detected by high-voltage current sensor to the sampling resistor being series in electromagnetic coil circuit, above-mentioned sampling resistor Number be n, n >=1, be that high-voltage current sensor is to the sampling after parallel connection by n identical sampling resistor parallel connection if n >=2 Resistance is sampled, and the dutycycle of the pwm signal of current sensor output is measured and then calculates detection current value, false If it is I to detect gained electric current by current sensor0, then it is I by the electric current of each sampling resistor1=I2=...=In=I0；
    Therefore, it is I by the actual current of magnet coil：
    I=I1+I2+…+In=nI0
    Wherein, n size determines according to the requirement in practical application to the scope and force feedback precision of force feedback.
  8. 8. coil current intelligent control method according to claim 7, it is characterised in that：In the step 5, use is adaptive Fuzzy PID algorithm is answered, the actual current in the magnet coil obtained to described current sample module carries out closed-loop control so that Electric current in coil with by the electric current that feedback force calculates in interactive application demand error range；
    Control for electric current in feedback of electromagnetic force device, the difference equation of pid number controller are：
    <mrow> <mi>u</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>K</mi> <mi>p</mi> </msub> <mi>e</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>+</mo> <msub> <mi>K</mi> <mi>i</mi> </msub> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>n</mi> <mo>=</mo> <mn>0</mn> </mrow> <mi>k</mi> </munderover> <mi>e</mi> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>+</mo> <msub> <mi>K</mi> <mi>d</mi> </msub> <mo>&amp;lsqb;</mo> <mi>e</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>-</mo> <mi>e</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>&amp;rsqb;</mo> </mrow>
    Wherein, u (k) is the electric current in the k moment magnet coils as obtained by regulation；E (k) is calculating gained electric current r (k) and sampling Electric current c (k) error signal, i.e. e (k)=r (k)-c (k), make ec(k) error rate for being current error signal e (k)；Kp、 Ki、KdRespectively PID ratios, integration and differential coefficient, make Δ kp、Δki、ΔkdParameter K during respectively adjustingp、Ki、Kd's Correction；Self-adaptive fuzzy algorithm is used to determine above-mentioned 3 parameter Kp、Ki、Kd；
    Self-adaptive fuzzy PID algorithm realizes comprising the following steps that for solenoid current intelligent control：
    Step 1：Choose the current error signal e and its error rate e of magnet coilcFor the input of fuzzy controller, output quantity For the correction amount k of pid parameterp、Δki、Δkd；
    Step 2：By the error originated from input e of fuzzy controller, its error rate ecWith the output Δ k of fuzzy controllerp、Δki、Δ kdIt is blurred, is respectively converted into fuzzy input variable E, Ec、ΔKp、ΔKi、ΔKd, choose membership function；
    Step 3：Suitable fuzzy reasoning table is established, obtains solenoid current pid control parameter correction amount Kp、ΔKi、ΔKd Fuzzy reasoning table；
    Step 4：The fuzzy reasoning table established according to step 3, to fuzzy input variable E, E of systemcFuzzy reasoning solves fuzzy close It is equation, obtains the fuzzy output amount of system；
    Step 5：The fuzzy output amount of step 4 is converted to by accurate output quantity by defuzzification method, then it is become through yardstick Get reality output amount Δ k in returnp、Δki、Δkd；
    Step 6：The increment of electric current in magnet coil is calculated, and the pwm signal of ARM Cortex-M3 outputs is adjusted, is turned Step 1；
    Above-mentioned self-adaptive fuzzy PID algorithm program is run in ARM Cortex-M3 embedded microcontrollers.
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