CN112356034B - Variable gain-based supercoiled sliding mode control method - Google Patents

Variable gain-based supercoiled sliding mode control method Download PDF

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CN112356034B
CN112356034B CN202011252672.3A CN202011252672A CN112356034B CN 112356034 B CN112356034 B CN 112356034B CN 202011252672 A CN202011252672 A CN 202011252672A CN 112356034 B CN112356034 B CN 112356034B
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CN112356034A (en
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邓华
胡蓉
张翼
夏睿恒
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Central South University
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/16—Programme controls
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
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Abstract

The invention discloses a variable gain-based supercoiled sliding mode control method which is mainly applied to control of multi-axis systems such as mechanical arms and the like; the power term gain in a general supercoiling algorithm is redesigned to be variable gain, new gain is used as the output of a first-order system, the absolute value of a sliding mode function is increased in proportion, the limited function is used as the input signal of the first-order system, and the violent change degree of the input signal is smoothed by utilizing the characteristic of low-pass filtering. The new gain has the following advantages: when the system state track is farthest away from the sliding mode switching surface, the variable gain is increased to the maximum value, so that the controller accelerates the system state track to approach the sliding mode switching surface with the maximum force; when the system state is in the quasi-sliding mode, the variable gain is attenuated to the minimum value, so that the controller fully inhibits the motion amplitude of the system state track by taking the sliding mode switching surface as the center, and the control input shake of the system is inhibited.

Description

Variable gain-based supercoiled sliding mode control method
Technical Field
The invention relates to a variable gain-based supercoiled sliding mode control method, which is mainly applied to multi-axis system control of mechanical arms and the like and belongs to the technical field of nonlinear control.
Background
The sliding mode control has excellent robustness, so that the sliding mode control can be widely applied in practice, such as speed control of a permanent magnet synchronous motor; position tracking control of the multi-axis mechanical arm; attitude control of the unmanned aerial vehicle, and the like. Generally, designing a sliding mode controller can be divided into two stages, namely designing a sliding mode function and designing an approach rate. The sliding mode function mainly affects the dynamic performance of the system in the sliding mode stage, and the approach rate mainly affects the performance of the system in the sliding mode arrival stage. A system strictly in the sliding mode is very robust against external disturbances. Therefore, the earlier the system state enters the sliding mode through the arrival stage, the better the robustness of the controller is, and the error is helped to be quickly converged.
Rate of approach at constant velocity
Figure GDA0003641736490000011
The simplest form is that, increasing the coefficient k, the motion point will reach the switching surface at a greater speed, and a sufficiently large k, although it can greatly shorten the reaching time, will cause severe shake. High-frequency dynamics are excited, mechanical aging is accelerated, control precision is reduced, and even system breakdown is caused. This is because the switching function in the approach rate is one of the key factors for ensuring the fast convergence of the system state trajectory in a limited time and the cause of jitter.
The suppression of trembling is largeTwo categories can be distinguished, one for suppressing jitter by adjusting k in real time: such as designing k as a function with respect to the sliding mode function s or introducing a fuzzy module; the key to applying this method is to select a function with a simple form and obvious effect. And the other type of the method ensures that the new approach rate can drive the system state track to be rapidly converged and effectively reduce the trembling by redesigning the switching function term: generally, the simplest method is to replace the switching function with a saturation function, and although this method can ensure control continuity and suppress chattering, it cannot strictly limit the dynamic state of the system on the sliding mode switching surface, and only ensures that the state converges into the boundary layer of the sliding mode switching surface. The switching function is hidden in a high-order term, so that shaking can be eliminated to a great extent, and after the system state enters a sliding mode, the control rate designed based on the method can ensure that the sliding mode function and the derivative thereof are converged to zero in a limited time. The algorithm of the super-helix is that,
Figure GDA0003641736490000012
the method is a special second-order sliding mode method, only sliding mode function information is needed, and the method is widely used for designing the controller. The traditional supercoiling algorithm cannot compensate the uncertain part which changes along with the state variable, and the time delay estimation algorithm can greatly simplify the design of the controller because an accurate system dynamics model is not required to be known. Therefore, the supercoiling algorithm can be well improved after the combination of the two. In addition, since ρ is being determined 1 And rho 3 When values are taken, unmodeled errors and interference need to be considered, the unmodeled errors and interference can be effectively compensated by time delay estimation, and rho is increased 1 And rho 3 And selecting a range of parameters.
The superspiral sliding mode algorithm includes power approaching rate
Figure GDA0003641736490000013
When the system state is far away from the sliding mode, the system can approach the sliding mode at a higher speed to increase rho 1 The effect of quick approach can be further enhanced, but the system state track is not completely positioned on the sliding mode switching surface after approaching the sliding mode switching surface, but tends to a stable point while performing switching motion along the sliding mode switching surface. Therefore, the larger the absolute value of the approach rate is, the larger the motion amplitude of the system state trajectory with the sliding mode switching surface as the center is, the more the robustness is affected, and the control input shake is aggravated. Therefore, how to effectively suppress the control input jitter while increasing the approach speed and ensuring the robustness is an urgent problem to be solved when the time delay estimation supercoiling control strategy is applied.
Disclosure of Invention
The technical problem solved by the invention is as follows: the method is based on a variable gain type super-spiral sliding mode control strategy, and is combined with an delay estimation calculation method, so that the system state can be driven to rapidly enter a sliding mode, the robustness of the system is improved, and the control input shake after the system state track approaches a sliding mode switching surface can be effectively inhibited.
The technical scheme adopted by the invention is that a variable gain type supercoiled sliding mode control strategy is implemented according to the following steps:
step 1, establishing a mathematical model of mechanical arm dynamics with n degrees of freedom:
Figure GDA0003641736490000021
Figure GDA0003641736490000022
wherein
Figure GDA0003641736490000023
Angular displacement, angular velocity and angular acceleration, respectively; m (q) epsilon R n×n In the form of a non-singular inertial matrix,
Figure GDA0003641736490000024
is a nominal part of the centrifuge and coriolis matrix; g 0 (q)∈R n Is the nominal portion of the gravity vector;
Figure GDA0003641736490000025
Figure GDA0003641736490000026
is the uncertainty part of the centrifuge and coriolis matrix; g u (q)∈R n Is the indeterminate portion of the gravity vector;
Figure GDA0003641736490000027
is a viscous friction torque vector at the joint; d, tau ∈ R n Respectively inputting a moment vector for interference;
Figure GDA0003641736490000028
error and interference are not modeled;
step 2, rewriting the formula (1) into the following mathematical model:
Figure GDA0003641736490000029
wherein:
Figure GDA00036417364900000210
Figure GDA00036417364900000211
is a constant diagonal matrix;
Figure GDA00036417364900000212
the undetermined parameter of the ith axis is a value range of: (0, 1); in selection of
Figure GDA00036417364900000213
The values are increased from small to large in sequence until the control effect begins to be poor because the values are large
Figure GDA00036417364900000214
The corresponding error is small. But is too large
Figure GDA00036417364900000215
Will amplify the noise, therefore
Figure GDA00036417364900000216
The selection of the value should give consideration to the requirements of good control effect and noise suppression;
step 3, designing a variable gain-based supercoiled sliding mode controller:
selecting displacement deviation as a system state variable: i.e. e ═ q d -q＝[q d1 -q 1 ,…,q dn -q n ]。
Wherein q is d ＝[q d1 q d2 …q dn ] T Representing a target angular displacement vector of the mechanical arm joint.
Selecting a linear sliding mode surface s as follows:
Figure GDA00036417364900000217
wherein c is a normal diagonal matrix;
from equation (5):
Figure GDA00036417364900000218
in order to reduce buffeting in sliding mode control, a control mode of a supercoiling algorithm is selected, namely:
Figure GDA0003641736490000031
from equations (6), (7), we can obtain:
Figure GDA0003641736490000032
wherein
Figure GDA0003641736490000033
Respectively estimating error and acceleration of time delay, and satisfying the following conditionsConditions are as follows:
Figure GDA0003641736490000034
sgn(s) represents a sign function,
Figure GDA0003641736490000035
in the invention, L in the formula (9) is the delay time of the delay estimation, according to the delay estimation theory, when L is small enough,
Figure GDA0003641736490000036
order to
Figure GDA0003641736490000037
Then
Figure GDA0003641736490000038
The conditions are satisfied:
Figure GDA0003641736490000039
delta is a positive real number vector;
in the present invention, μ ═ diag (μ) in formula (7) 1 ,…,μ n ) For the first order system input signal | s h The amplification gain of |, a ═ diag (a), can be adjusted according to the actual demand 1 ,…,a n ) Is directly opposite to the angular matrix, and a i >1; the time constant of this first order system is: t1/rho 0 Where ρ is 0 ＝diag(ρ 01 ,…,ρ 0n ) Is a positive diagonal matrix; let the initial value of θ be: θ (0) ═ diag (ρ) 11 ,…,ρ 1n ) Since overshoot is not possible in the first order system, the value of theta does not exceed ap 1 Setting an input signal | s h Cutoff value of and ρ 1 The correlation is to limit θ max And give consideration to rho 3 Taking the value of (A); the variation range of theta satisfies: theta (t) epsilon [ rho ] 1 ，aρ 1 ](ii) a The time taken for θ (t) to reach 98% of the input signal is: 4 x 1/[ rho ] 0 ；ρ 1 ＝[ρ 11 ,…,ρ 1n ] T Is a constant vector; ρ is a unit of a gradient 3 ＝diag(ρ 31 ,…,ρ 3n ) Is directly opposite to the angular matrix, and rho 1 The value range of (A) satisfies:
ρ 1 ＞0
Figure GDA00036417364900000310
Figure GDA00036417364900000311
in the invention, after the provided supercoiling algorithm is combined with the time delay estimation algorithm, the delta value is smaller, so that rho is enabled to be 3 The value can be further reduced, when the planned trajectory varies by a small amount, p 1 And rho 3 A smaller value can be obtained, and shake after the system state track approaches the sliding mode switching surface is better inhibited;
in the present invention, the parameter ρ 1 ，ρ 3 ，μ，a,ρ 0 The selection steps are as follows: increase a, p starting from 0 1 And rho 3 Value, observing control effect, regulating mu and rho according to variation trend of sliding mode function 0 Ensuring that the state track of the system quickly approaches to the sliding mode switching surface; large a, mu, rho 0 ,ρ 3 High control accuracy can be ensured, but if the control accuracy is increased inappropriately, the system dynamics performance is deteriorated.
By adopting the technical scheme, the invention has the following technical effects:
1. the variable gain is introduced into the controller, so that the problem that the acceleration system reaches a sliding mode, the robustness is guaranteed, and the jitter of the input control cannot be effectively inhibited is solved, the response speed is improved, the power term is further enhanced to quickly approach a sliding mode switching surface, and the jitter is effectively inhibited, particularly when the system is in a quasi-sliding mode;
2. the method is combined with a time delay estimation strategy, and can adapt to the excellent characteristic of time-varying interference;
3. the newly introduced variable gain is simple to solve and does not significantly increase the complexity of the controller.
Drawings
FIG. 1 is a structural diagram of a variable gain-based supercoiled sliding mode control according to the present invention.
FIG. 2 is a diagram of a variable gain-based super-helical sliding mode control input planning trajectory according to the present invention.
FIG. 3 is a waveform diagram of a variable gain-based tracking error of the control axis of the supercoiled sliding mode.
FIG. 4 is a time-domain variation waveform diagram of a sliding mode function of a control axis of a supercoiled sliding mode based on variable gain according to the present invention.
FIG. 5 is a time-domain variation waveform diagram of a moment required by a control shaft of a supercoiled sliding mode based on variable gain according to the present invention.
FIG. 6 is a waveform diagram of a variable gain based superhelical sliding mode control axis two tracking error in the present invention.
FIG. 7 is a time-domain variation waveform diagram of two sliding mode functions of a super-helical sliding mode control shaft based on variable gain in the invention.
FIG. 8 is a time-domain variation waveform diagram of a moment required by a second variable-gain-based supercoiled sliding mode control shaft.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
The invention discloses a variable gain-based supercoiled sliding mode control method which is mainly applied to control of multi-axis systems such as mechanical arms. The power term gain in a general supercoiling algorithm is redesigned to be variable gain, new gain is used as the output of a first-order system, the absolute value of a sliding mode function is increased in proportion, the limited function is used as the input signal of the first-order system, and the violent change degree of the input signal is smoothed by utilizing the characteristic of low-pass filtering. The new gain has the following advantages: when the system state track is farthest away from the sliding mode switching surface, the variable gain is increased to the maximum value, so that the controller accelerates the system state track to approach the sliding mode switching surface with the maximum force; when the system state is in the quasi-sliding mode, the variable gain is attenuated to the minimum value, so that the controller fully inhibits the motion amplitude of the system state track by taking the sliding mode switching surface as a central surface, and the control input shake of the system is inhibited.
Taking an n-degree-of-freedom mechanical arm as an example, the method comprises the following specific steps:
step 1, establishing a mathematical model of mechanical arm dynamics with n degrees of freedom:
Figure GDA0003641736490000041
Figure GDA0003641736490000042
wherein
Figure GDA0003641736490000043
Angular displacement, angular velocity and angular acceleration, respectively; m (q) epsilon R n×n In the form of a non-singular inertial matrix,
Figure GDA0003641736490000044
is a nominal part of the centrifuge and coriolis matrix; g 0 (q)∈R n Is the nominal portion of the gravity vector;
Figure GDA0003641736490000045
Figure GDA0003641736490000046
is the uncertainty part of the centrifuge and coriolis matrix; g u (q)∈R n Is the indeterminate portion of the gravity vector;
Figure GDA0003641736490000047
is a viscous friction torque vector at the joint; d, tau ∈ R n Respectively inputting a moment vector for interference;
Figure GDA0003641736490000048
error and interference are not modeled;
step 2, rewriting the formula (1) into the following mathematical model:
Figure GDA0003641736490000049
wherein:
Figure GDA00036417364900000410
Figure GDA0003641736490000051
a constant diagonal matrix;
Figure GDA0003641736490000052
the undetermined parameter of the ith axis is the value range of: (0, 1); in selection of
Figure GDA0003641736490000053
The values are increased from small to large in sequence until the control effect begins to be poor because the values are large
Figure GDA0003641736490000054
The corresponding error is small. But is too large
Figure GDA0003641736490000055
Will amplify the noise, therefore
Figure GDA0003641736490000056
The selection of the value should give consideration to the requirements of good control effect and noise suppression;
and 3, designing a variable gain-based supercoiled sliding mode controller:
selecting displacement deviation as a system state variable: i.e. e ═ q d -q＝[q d1 -q 1 ,…,q dn -q n ]。
Wherein q is d ＝[q d1 q d2 …q dn ] T Representing a target angular displacement vector of the mechanical arm joint.
Selecting a linear sliding mode surface s as follows:
Figure GDA0003641736490000057
wherein c is a normal diagonal matrix;
from equation (5):
Figure GDA0003641736490000058
in order to reduce buffeting in sliding mode control, a control mode of a supercoiling algorithm is selected, namely:
Figure GDA0003641736490000059
from equations (6), (7), we can obtain:
Figure GDA00036417364900000510
wherein
Figure GDA00036417364900000511
Respectively estimating errors and acceleration of the time delay, and meeting the following conditions:
Figure GDA00036417364900000512
sgn(s) represents a sign function,
Figure GDA00036417364900000513
in the invention, L in the formula (9) is the delay time of the delay estimation, and according to the delay estimation theory, when L is sufficientWhen the size of the bag is small enough,
Figure GDA00036417364900000514
order to
Figure GDA00036417364900000515
Then
Figure GDA00036417364900000516
The conditions are satisfied:
Figure GDA00036417364900000517
delta is a positive real number vector;
in the present invention, μ ═ diag (μ) in formula (7) 1 ,…,μ n ) For the first order system input signal | s h The amplification gain of |, a ═ diag (a), can be adjusted according to the actual demand 1 ,…,a n ) Is directly opposite to the angular matrix, and a i >1; the time constant of this first order system is: t1/rho 0 Where ρ is 0 ＝diag(ρ 01 ,…,ρ 0n ) Is a positive diagonal matrix; let the initial value of θ be: θ (0) ═ diag (ρ) 11 ,…,ρ 1n ) Since overshoot is not possible in the first order system, the value of theta does not exceed ap 1 Setting an input signal | s h Cutoff value of and ρ 1 The correlation is to limit θ max And give consideration to rho 3 Taking the value of (A); the variation range of theta satisfies: theta (t) epsilon [ rho ] 1 ，aρ 1 ](ii) a The time taken for θ (t) to reach 98% of the input signal is: 4 x 1/[ rho ] 0 ；ρ 1 ＝[ρ 11 ,…,ρ 1n ] T Is a constant vector; rho 3 ＝diag(ρ 31 ,…,ρ 3n ) Is directly opposite to the angular matrix, and rho 1 The value range of (A) satisfies:
ρ 1 ＞0
Figure GDA0003641736490000061
Figure GDA0003641736490000062
in the invention, after the provided supercoiling algorithm is combined with the time delay estimation algorithm, the delta value is smaller, so that rho is enabled to be 3 The value can be further reduced, when the planned trajectory varies by a small amount, p 1 And rho 3 A smaller value can be obtained, and shake after the system state track approaches the sliding mode switching surface is better inhibited;
in the present invention, the parameter ρ 1 ，ρ 3 ，μ，a,ρ 0 The selection steps are as follows: increase a, p starting from 0 1 And rho 3 Value, observing control effect, regulating mu and rho according to variation trend of sliding mode function 0 Ensuring that the state track of the system quickly approaches to the sliding mode switching surface; larger a, μ, ρ 0 ,ρ 3 Values can guarantee high control accuracy, but if improperly increased, can lead to poor system dynamics.
After simulation, the result is shown in fig. 1-8, the sliding mode functions of the two shafts approach the quasi-sliding mode internally, and the variable gain type super-spiral sliding mode control strategy has better performance.
The above embodiments are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modifications made on the basis of the technical scheme according to the technical idea of the present invention fall within the protection scope of the present invention.

Claims (1)

1. A variable gain-based supercoiling sliding mode control method is characterized by comprising the following steps:
step 1, establishing a mathematical model of mechanical arm dynamics with n degrees of freedom:
Figure FDA0003641736480000011
Figure FDA0003641736480000012
wherein the ratio of q,
Figure FDA0003641736480000013
angular displacement, angular velocity and angular acceleration, respectively; m (q) epsilon R n×n In the form of a non-singular inertial matrix,
Figure FDA0003641736480000014
is a nominal part of the centrifuge and coriolis matrix; g 0 (q)∈R n Is the nominal portion of the gravity vector;
Figure FDA0003641736480000015
Figure FDA0003641736480000016
is the uncertainty part of the centrifuge and coriolis matrix; g u (q)∈R n Is the uncertain part of the gravity vector;
Figure FDA0003641736480000017
is a viscous friction torque vector at the joint; d, tau ∈ R n Respectively inputting a moment vector for interference;
Figure FDA0003641736480000018
error and interference are not modeled;
step 2, rewriting the formula (1) into the following mathematical model:
Figure FDA0003641736480000019
wherein:
Figure FDA00036417364800000110
Figure FDA00036417364800000111
is a constant diagonal matrix;
Figure FDA00036417364800000112
the undetermined parameter of the ith axis is the value range of: (0, 1); in selection of
Figure FDA00036417364800000113
The values are increased from small to large in sequence until the control effect begins to be poor because the values are large
Figure FDA00036417364800000114
Corresponding errors being small but too large
Figure FDA00036417364800000115
Will amplify the noise, therefore
Figure FDA00036417364800000116
The selection of the value should give consideration to the requirements of good control effect and noise suppression;
and 3, designing a variable gain-based supercoiled sliding mode controller:
selecting displacement deviation as a system state variable: i.e. e ═ q d -q＝[q d1 -q 1 ,…,q dn -q n ]；
Wherein q is d ＝[q d1 q d2 …q dn ] T Representing a target angular displacement vector of a mechanical arm joint;
selecting a linear sliding mode surface s as follows:
Figure FDA00036417364800000117
wherein c is a normal diagonal matrix;
from equation (5):
Figure FDA00036417364800000118
in order to reduce buffeting in sliding mode control, a control mode of a supercoiling algorithm is selected, namely:
Figure FDA00036417364800000119
from equations (6), (7), we can obtain:
Figure FDA0003641736480000021
wherein
Figure FDA0003641736480000022
Respectively estimating errors and acceleration of the time delay, and meeting the following conditions:
Figure FDA0003641736480000023
sgn(s) represents a sign function,
Figure FDA0003641736480000024
in equation (9), L is the delay time of the delay estimation, and according to the delay estimation theory, when L is small enough,
Figure FDA0003641736480000025
order to
Figure FDA0003641736480000026
Then the
Figure FDA0003641736480000027
The conditions are satisfied:
Figure FDA0003641736480000028
delta is a positive real number vector;
μ ═ diag (μ) in formula (7) 1 ,…,μ n ) For the first order system input signal | s h The amplification gain of |, a ═ diag (a), can be adjusted according to the actual demand 1 ,…,a n ) Is directly opposite to the angular matrix, and a i >1; the time constant of this first order system is: t1/rho 0 Where ρ is 0 ＝diag(ρ 01 ,…,ρ 0n ) Is a positive diagonal matrix; let the initial value of θ be: θ (0) ═ diag (ρ) 11 ,…,ρ 1n ) Since overshoot is not possible in the first order system, the value of theta does not exceed ap 1 Setting an input signal | s h Cutoff value of and ρ 1 The correlation is to limit θ max And give consideration to rho 3 Taking the value of (A); the variation range of theta satisfies: theta (t) epsilon [ rho ] 1 ，aρ 1 ](ii) a The time taken for θ (t) to reach 98% of the input signal is: 4 x 1/[ rho ] 0 ；ρ 1 ＝[ρ 11 ,…,ρ 1n ] T Is a constant vector; rho 3 ＝diag(ρ 31 ,…,ρ 3n ) Is directly aligned with the angular matrix, and rho 1 The value range of (A) satisfies:
ρ 1 ＞0
Figure FDA0003641736480000029
Figure FDA00036417364800000210
after the proposed supercoiling algorithm is combined with the time delay estimation algorithm, the value of delta is smaller, so that rho 3 The value can be further reduced, when the planned trajectory varies by a small amount, p 1 And rho 3 A smaller value can be obtained, and shake after the system state track approaches the sliding mode switching surface is better inhibited;
parameter p 1 ，ρ 3 ，μ，a,ρ 0 The selection steps are as follows:increase a, p starting from 0 1 And rho 3 Value, observing control effect, regulating mu and rho according to variation trend of sliding mode function 0 Ensuring that the state track of the system quickly approaches to the sliding mode switching surface; larger a, μ, ρ 0 ,ρ 3 Values can guarantee high control accuracy, but if improperly increased, can lead to poor system dynamics.
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104917436A (en) * 2015-07-08 2015-09-16 沈阳工业大学 Adaptive second-order terminal sliding-mode control system and method of permanent magnet linear synchronous motor
CN107102634A (en) * 2017-05-11 2017-08-29 北京理工大学 A kind of parameter Estimation and tracking and controlling method based on table servo system
CN107255922A (en) * 2017-05-27 2017-10-17 燕山大学 A kind of fast turn of speed method of estimation of remote control system based on adaptive double-deck sliding formwork
CN107370436A (en) * 2017-06-27 2017-11-21 上海电机学院 A kind of direct Torque Control based on Super twisting sliding formworks
CN109656132A (en) * 2018-07-26 2019-04-19 西北工业大学 A kind of robot for space finite time control method for coordinating

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104917436A (en) * 2015-07-08 2015-09-16 沈阳工业大学 Adaptive second-order terminal sliding-mode control system and method of permanent magnet linear synchronous motor
CN107102634A (en) * 2017-05-11 2017-08-29 北京理工大学 A kind of parameter Estimation and tracking and controlling method based on table servo system
CN107255922A (en) * 2017-05-27 2017-10-17 燕山大学 A kind of fast turn of speed method of estimation of remote control system based on adaptive double-deck sliding formwork
CN107370436A (en) * 2017-06-27 2017-11-21 上海电机学院 A kind of direct Torque Control based on Super twisting sliding formworks
CN109656132A (en) * 2018-07-26 2019-04-19 西北工业大学 A kind of robot for space finite time control method for coordinating

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