CN116160455B - Dynamic event triggering and quantization control method for single-arm manipulator under multi-channel attack - Google Patents
Dynamic event triggering and quantization control method for single-arm manipulator under multi-channel attack Download PDFInfo
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Abstract
The invention discloses a dynamic event triggering and quantization control method of a single-arm manipulator under multichannel attack, and relates to the technical field of single-arm manipulator control. The problem of stability of the single-arm manipulator under the condition of multi-channel attack is solved, and the problem of excessive network communication resource waste is solved by adopting event triggering, quantitative control and the like. S1, establishing a state space equation obeying Markov jump; s2, providing an asynchronous output feedback controller based on a dynamic event trigger mechanism and a quantization strategy; s3, solving a controller gain matrix; and S4, under the multi-channel attack, the output angle and the output angular speed of the single-arm manipulator are controlled through the output feedback controller designed in the S3, so that the single-arm manipulator control system is randomly stable, and strict dissipation is met. The invention improves the stability and strict dissipation performance of the closed-loop system of the single-arm manipulator under the random condition, and can save precious network communication resources in the network communication process.
Description
Technical Field
The invention relates to the technical field of control of single-arm manipulators, in particular to dynamic event triggering and quantitative control of a Markov jump system of a single-arm manipulator under multi-channel attack.
Background
With the change of enterprises and the pursuit of people for high-quality life, single-arm manipulators move into the production and life of people. The single-arm manipulator is used as one of important tools for industrial automation, and is composed of a lifting hook, a box-type telescopic arm, a telescopic chain, a base, a rotating device, a supporting device and the like, and compared with other types of manipulators, the single-arm manipulator occupies smaller working space, and plays a vital role in the aspects of enhancing the safety of workers, improving the living comfort of people and the like. At present, a single-arm manipulator is additionally provided with a plurality of networked control devices, so that the manipulator can be continuously adjusted in a complex industrial environment, and the influence of the complex industrial environment on the manipulator is reduced. Therefore, single-arm robots have become a trend of industrial robots, and are one of the hot problems in many researches.
There are related technologies related to single arm manipulators, and there are few concerns about randomness, safety and energy consumption of the system, and the shortcomings are mainly represented in the following aspects:
1) The model of the single arm manipulator does not take into account the random factors in the actual production process. In order to facilitate theoretical design and analysis, people often neglect complex multi-mode systems in actual operation. In an actual working environment, the single-arm manipulator often has the conditions that parameters of elements are changed and the working environment is suddenly changed, so that the manipulator component is failed or is effective, and the manipulator cannot work normally.
2) The control of conventional single-arm robots typically suffers from excessive energy waste and information redundancy. Unlike continuous time sampling robots, conventional robots typically sample at fixed intervals, so that many unnecessary communication resources are consumed at fixed points in time, increasing network communication burden and reducing work efficiency.
3) In the prior art related to the single-arm manipulator, the networking safety problem is less considered. In an actual network control communication system, there is inevitably an attack phenomenon in communication between a controller and a sensor, an actuator, and the like. Wherein a spoofing attack may tamper with the signal given by the sensor, which may have a great impact on the feedback control.
Based on the above situation, the Chinese patent application with publication date of 2019, 2-15 and publication number of CN109333529A discloses a structure and a design method of a multi-single-arm manipulator output consistent active disturbance rejection controller with preset performance. The method mainly comprises the following steps: 1) And constructing a state model of the single-arm manipulator. 2) And taking the position state of the single-arm manipulator as control output, and analyzing the convergence speed of the output consistent error and the anti-interference performance of the system for the single-arm manipulator. 3) A multi-single arm manipulator output consistent controller with predefined performance is designed. The method can improve the anti-interference capability of the single-arm manipulator through compensation. However, the technical scheme has the following defects: 1) The single-arm manipulator model does not consider the problem of energy waste, and communication burden between channels possibly exists, so that compared with a manipulator with dynamic event triggering, the single-arm manipulator model is more energy-saving and has better economic benefit. 2) The designed single-arm manipulator system does not consider the problem of networking security, for example: the influence of the networked attack can not guarantee the safety in the application to the practical single-arm manipulator system.
In addition, the Chinese patent application with the publication date of 2022, 3 month and 15 days and the publication number of CN114179115A discloses a single-arm manipulator self-adaptive forward output consistent controller, which comprises the steps of establishing a state space equation of the multi-single-arm manipulator, considering a dynamic event triggering unit and designing a controller under the condition of faults and the like, and realizing the safety control of the single-arm manipulator. But this technique also has drawbacks: 1) The modeling does not consider random factors, and the abrupt change situation of the actual working state cannot be accurately dealt with. 2) The energy waste and the information redundancy are not comprehensive, and the communication burden can be further reduced by adopting the quantized data to transmit in a coded form. 3) The lack of consideration to the network security of the system ensures the security of the system.
Disclosure of Invention
Aiming at the problems, the invention provides a dynamic event triggering and quantization control method of a single-arm manipulator under multi-channel attack, so as to solve the stability problem of the single-arm manipulator under the multi-channel attack condition, and solve the problem of excessive network communication resource waste by adopting event triggering, quantization control and the like. Consider Markov models, multi-channel attacks, event triggers, and quantized control cases. The Markov jump system can be used to describe the phenomenon that a dynamic system changes suddenly; in the intelligent network control, the event triggering and the quantization control can save communication resources. The invention improves the stability and strict dissipation performance of the closed-loop system of the single-arm manipulator under the random condition, and can save precious network communication resources in the network communication process.
The technical scheme of the invention is as follows: the method comprises the following steps:
s1, establishing a state space equation obeying Markov jump according to a mechanical model of a single-arm manipulator;
s2, for a mathematical model of the single-arm manipulator in the step S1, a novel asynchronous output feedback controller based on a dynamic event trigger mechanism and a quantization strategy is provided for a Markov jump system with multi-channel random spoofing attack;
s3, designing asynchronous output feedback control, and establishing a closed-loop control system; based on Lyapunov theory, establishing sufficiency conditions to ensure random stability and strict dissipation of the closed-loop system, and solving a controller gain matrix;
and S4, under the multi-channel attack, controlling the output angle and the output angular speed of the single-arm manipulator through the asynchronous output feedback controller designed in the step S3, so that the single-arm manipulator control system is randomly stable, and the strict dissipation performance is met.
Further, the method for establishing the model of the single-arm manipulator subject to Markov jump in step S1 is specifically as follows:
the dynamic equation of the single-arm manipulator is established as follows:
wherein θ is the output angle, Q is the moment of inertia, D (t) is the viscous coefficient of friction of the joint rotation, mglsin (θ) is the gravitational term of the single link mechanical arm, u is the control moment of the single link mechanical arm, M is the mass of the payload, g is the gravitational acceleration, and l is the length of the arm;
selecting x 1 (t) =θ is the output angle of the single arm manipulator,to output angular velocity and satisfy X (t) is selected as the system state, y (t) is selected as the output position signal, u (t) is the control input, and ω (t) is the external disturbance.
Considering the change of the parameters or the structure of the system, the state equation of the single-arm manipulator is assumed to be that the system is subjected to random Markov jump:
wherein the matrix x (t), A, B, C, D 0 The definition is as follows:
further, after the measurement output of the system is considered, the state equation of the single-arm manipulator Markov jump system can be obtained as follows:
where x (t) is the system state, y (t) is the system output, u (t) is the control input, z (t) is the measurement output, ω (t) is the external disturbance. Lambda (t), t>0 denotes a Markov process defined on a complete probability space, in a finite setThe transition probability matrix is +.>The transition probability is as follows:
wherein whenρ αl The transfer rate of the system from the alpha mode at time t to the l mode at time t+delta t is shown by +.>
The design of the asynchronous output feedback controller based on the hidden Markov model in the step S2 obtains a Markov jump closed loop system under the multi-channel attack of dynamic event triggering and quantification, and the specific method is as follows:
the dynamic event triggering mechanism is designed as follows:wherein,y(t k h)，kh，t k h is the transmitted sampling data, sampling time and latest trigger time, J 1 (λ(t))>0，J 2 (λ(t))>0 is a modal dependent weight matrix, v>0 is a given constant, δ (λ (t))e (0, 1) is a given modality dependent threshold parameter. The internal dynamic variable η (t) satisfies:m>0,χ>0, and eta (t) 0 )＝η 0 ≥0。
In addition, since the communication channel has a limited bandwidth, the transmitted signal is quantized by the quantizer, so as to reduce the transmission load of the signal, and the output signal y (t k h) The logarithmic quantizer q used for quantization is passed through a quantizer before being transmitted to the actuator ι (-) is:
wherein,for arbitrary quantization errorsThe quantized output expression obtained by the sector boundary method is:
wherein,definition of the definition
To overcome the vulnerability of single channels, the present invention employs a multi-channel transmission strategy. At the same time, it is considered that each transport channel may be subject to different network attacks. HMM-based transmission schedulert≥0，f t Representing the total number of transmission channels, the scheduler pi (t) satisfies a pre-known conditional probability matrix +.>Expressed as:
wherein ζ is 0- ζ αr Is less than or equal to 1Based on the modal information of the system, at each transmission time instant, the scheduler selects only one channel to transmit data.
In network communication, a spoofing attack often occurs, an attack signal is injected into a channel between a sensor and a controller to replace original signal information, and assuming that an attacker can capture system dynamics and release an aggressive signal in a random manner, system information acquired by the controller under the influence of the attack signal is as follows:
the asynchronous output feedback controller based on the HMM is as follows:
u(t)＝K v {q(y(t k h))+β r (t)[-q(y(t k h))+a r (y(t))]} (10)
wherein K is v For the controller gain matrix, beta r (t) ∈ {0,1} represents Bernoulli procedure for characterizing whether or not a spoofing attack occurs at time t, a r (y (t)) represents attack signals released in a random manner, q (y (t) k h) A) represents the captured system dynamics. In addition, ρ (t), t is equal to or greater than 0, is a Markov process, and satisfies a conditional probability matrixAnd conditional probabilities are described as follows:
wherein,
substituting (10) into (3) to obtain the Markov jump closed-loop control system under the multi-channel attack containing dynamic event triggering and quantization, wherein the Markov jump closed-loop control system comprises the following steps:
the random stability of the design single arm manipulator mentioned in step S3 is as follows:
this condition is satisfied, then the system (12) is randomly stable when ω (t) ≡0.
Likewise, the designed single arm robot dissipation performance mentioned in step S3 is as follows:
if this condition is satisfied, the closed loop system (12) is strict (ψ 1 ,ψ 2 ,ψ 3 ) -gamma-dissipative.
Wherein J (z (t), ω (t))=z T ψ 1 z(t)+2z T ψ 2 ω(t)+ω T (t)ψ 3 ω(t)，Gamma is the dissipative property index.
The invention considers the problems of communication attack, part parameter change, large energy consumption and the like of an actual single-arm manipulator, and the traditional controller cannot solve the influence of the factors, and provides a novel asynchronous output feedback controller based on a dynamic event triggering and quantization strategy for the Markov jump system with the multichannel random spoofing attack for the first time. And unlike existing spoofing attacks, the present invention randomly presents a spoofing attack in each channel. The stability and the strict dissipation performance of the closed-loop system of the single-arm manipulator under the random condition are improved, and precious network communication resources can be saved in the network communication process.
Drawings
FIG. 1 is a flow chart of an asynchronous output feedback control method of a single arm manipulator system in an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of a single arm manipulator system in an embodiment of the present disclosure;
FIG. 3 is an event trigger timing of a single arm manipulator system in an embodiment of the present disclosure;
FIG. 4 is a signal of a single arm manipulator system channel being attacked in an embodiment of the present disclosure;
FIG. 5 is a diagram of information about each mode of a single arm manipulator system in an embodiment of the present disclosure;
FIG. 6 is a system output of a single arm robotic system in an embodiment of the present disclosure;
fig. 7 is a control input of a single arm robot system in an embodiment of the present disclosure.
Detailed Description
In order to clearly illustrate the technical features of the present patent, the following detailed description will make reference to the accompanying drawings.
The invention provides a Markov jump dynamic event triggering and quantifying controller of a single-arm manipulator under multi-channel attack, which aims to improve the non-vulnerability of a transmission channel of the single-arm manipulator under networked control, reduce the situations of energy waste caused by overlarge burden and continuous work of a communication channel in a shared network, and simultaneously aim to cope with the situations that the state of the single-arm manipulator is changed and the controllers are not synchronous during work.
Examples:
as shown in fig. 1, the method comprises the following steps:
s1, establishing a state space equation obeying Markov jump according to a mechanical model of a single-arm manipulator;
the specific method for establishing the model of the single-arm manipulator obeying Markov jump comprises the following steps:
as shown in fig. 2, from the physical model of the single arm manipulator, a dynamic equation is established:
wherein θ is the output angle, Q is the moment of inertia, D (t) is the viscous coefficient of friction of joint rotation, mgl sin (θ) is the gravitational term of the single-link mechanical arm, u is the control moment of the single-link mechanical arm, M is the mass of the payload, g is the gravitational acceleration, and l is the length of the arm;
selecting x 1 (t) =θ is the output angle of the single arm manipulator,to output angular velocity and satisfy X (t) is selected as the system state, y (t) is the output position signal, u (t) is the control input, and ω (t) is the external disturbance.
Considering the change of the parameters or the structure of the system, the state equation of the single-arm manipulator is assumed to be that the system is subjected to random Markov jump:
wherein the matrix x (t), A, B, C, D 0 The definition is as follows:
further, after the measurement output of the system is considered, the state equation of the single-arm manipulator Markov jump system can be obtained as follows:
where x (t) is the system state, y (t) is the system output, u (t) is the control input, z (t) is the measurement output, ω (t) is the external disturbance. Lambda (t), t>0 denotes a Markov process defined on a complete probability space, in a finite setIn the middle value, transition probability matrix->The transition probability is as follows:
wherein whenρ αl The transfer rate of the system from the alpha mode at time t to the l mode at time t+delta t is shown by +.>
S2, designing an asynchronous output feedback controller based on a hidden Markov model for the mathematical model of the single-arm manipulator in the step S1 to obtain a Markov jump closed-loop system under the multi-channel attack of dynamic event triggering and quantization;
the dynamic event triggering mechanism is designed as follows:wherein,y(t k h)，kh，t k h is the transmitted sampling data, sampling time and latest trigger time, J 1 (λ(t))>0，J 2 (λ(t))>0 is a modal dependent weight matrix, v>0 is a given constant, δ (λ (t))e (0, 1) is a given modality dependent threshold parameter. The internal dynamic variable η (t) satisfies:m>0,χ>0, and eta (t) 0 )＝η 0 ≥0。
In addition, since the communication channel has a limited bandwidth, the transmitted signal is quantized by the quantizer, so as to reduce the transmission load of the signal, and the output signal y (t k h) The logarithmic quantizer q used for quantization is passed through a quantizer before being transmitted to the actuator ι (-) is:
wherein,for any quantization error, the quantized output expression is obtained by a sector boundary method as follows:
wherein,
definition of the definition
To overcome the vulnerability of single channels, the present invention employs a multi-channel transmission strategy. At the same time, it is considered that each transport channel may be subject to different network attacks. HMM-based transmission schedulert≥0，f t Representing the total number of transmission channels, the scheduler pi (t) satisfies a pre-known conditional probability matrix +.>Expressed as:
wherein ζ is 0- ζ αr Is less than or equal to 1Based on the modal information of the system, at each transmission time instant, the scheduler selects only one channel to transmit data.
In network communication, a spoofing attack often occurs, an attack signal is injected into a channel between a sensor and a controller to replace original signal information, and assuming that an attacker can capture system dynamics and release an aggressive signal in a random manner, system information acquired by the controller under the influence of the attack signal is as follows:
the asynchronous output feedback controller based on the HMM is as follows:
u(t)＝K v {q(y(t k h))+β r (t)[-q(y(t k h))+a r (y(t))]} (10)
wherein K is v For the controller gain matrix, beta r (t) ∈ {0,1} represents Bernoulli procedure for characterizing whether or not a spoofing attack occurs at time t, a r (y (t)) represents attack signals released in a random manner, q (y (t) k h) A) represents the captured system dynamics. In addition, ρ (t), t is equal to or greater than 0, is a Markov process, and satisfies a conditional probability matrixAnd conditional probabilities are described as follows:
wherein,
substituting (10) into (3) to obtain the Markov jump closed-loop control system under the multi-channel attack containing dynamic event triggering and quantization, wherein the Markov jump closed-loop control system comprises the following steps:
the system random stability requirements are as follows:
this condition is satisfied, then the system (12) is randomly stable when ω (t) ≡0.
Likewise, the system dissipation performance is as follows:
if this condition is satisfied, the closed loop system (12) is strict (ψ 1 ,ψ 2 ,ψ 3 ) -gamma-dissipative.
Wherein J (z (t), ω (t))=z T ψ 1 z(t)+2z T ψ 2 ω(t)+ω T (t)ψ 3 ω(t)，Gamma is the dissipative property index.
S3, establishing sufficiency conditions to ensure random stability of the Markov jump closed-loop control system and meet strict dissipation based on the Lyapunov theory according to the Markov jump closed-loop control system under the multi-channel attack containing dynamic event triggering and quantization described in the step S2, and solving the gain of the controller by adopting an LMI toolbox of MTALAB, wherein the specific process is as follows:
based on Lyapunov theory, the sufficient conditions for ensuring the random stability of the Markov jump closed-loop control system and meeting strict dissipation are as follows:
for a given parameter τ M >0，δ α ∈[0,1)，Sum-real matrix If matrix P is present α >0,R>0,Q>0,H>0,J 1α >0,J 2α >0,W avr >0, N, Y, for any +.>So that (14), (15), (16) are true:
wherein,
the closed loop control system (12) is randomly stable and satisfies the stringent (ψ) 1 ,ψ 2 ,ψ 3 ) -gamma-dissipative properties.
According to the inequality of the linear matrix, the controller gain is solved as follows:
for a given parameter τ M >0,δ α ∈[0,1),Sum-real matrixIf matrix P is present α >0,R>0,Q>0,H>0,J 1α >0,J 2α >0,W avr >0,N,Y,Z υ ,χ υ Parameter epsilon>0, for arbitrary->So that inequalities (14), (15) and the following are established:
wherein,
the controller gain matrix may be:
the closed loop control system (12) is randomly stable and satisfies the stringent (ψ) 1 ,ψ 2 ,ψ 3 ) -gamma-dissipative properties.
For the single arm manipulator system as shown in fig. 2, the parameters l=0.5, g=9.81, d are chosen 0 ＝2，A{1}＝[0,1；-9.81*0.5,-0.2*2]；A{2}＝[0,1；-9.81*0.5,-2]；B{1}＝[1.4387；0]；B{2}＝[0.5755；0]；C{1}＝[1；0]；C{2}＝[1；0]；D{1}＝[1 0]；D{2}＝[1 0]；F 1 ＝F 2 ＝0.1，E 1 ＝E 2 ＝[0,1]，ρ＝[-2,2；3,-3]，ψ＝[0.6 0.4；0.3 0.7]The method comprises the steps of carrying out a first treatment on the surface of the The controller gain obtained by the algorithm is as follows: k (K) 1 ＝-0.0428,K 2 ＝-0.0399。
Fig. 3 is a diagram illustrating the time of event triggering of the single arm manipulator system according to the embodiment of the present invention, and it can be clearly seen from the diagram that the dynamic event triggering mechanism of the present invention is effective.
Fig. 4 shows signals of the single arm manipulator system channel of the invention, and the attack situation can be clearly understood from the change of the curve.
Fig. 5 is information of each mode of the single arm manipulator system according to the embodiment of the invention, and the mode change condition of the single arm manipulator system based on Markov jump can be seen from a simulation diagram.
Fig. 6 shows the system output of the single arm manipulator system of the invention example, and the simulation result shows that the asynchronous output feedback controller designed by the invention is stable finally, and the effectiveness of the controller is verified.
Fig. 7 is a control input diagram of a single arm manipulator system of an example of the invention, from which the transition from the system output curve can be clearly observed.
The invention selects the continuous model of the single-arm manipulator under the multi-channel attack of dynamic event triggering and quantization control as a research object, solves the safety problem that the communication burden and the actual work are not considered in the prior art, and provides a novel asynchronous output feedback controller based on the dynamic event triggering and quantization strategy, so that the system output can reach a stable state even if the system has the external multi-channel attack and the condition of overlarge communication burden.
While there have been described what are believed to be the preferred embodiments of the present invention, it will be apparent to those skilled in the art that many more modifications are possible without departing from the principles of the invention.
Claims (2)
1. The dynamic event triggering and quantization control method of the single-arm manipulator under the multi-channel attack is characterized by comprising the following steps:
s1, establishing a state space equation obeying Markov jump according to a mechanical model of a single-arm manipulator;
s2, designing an asynchronous output feedback controller based on a dynamic event trigger mechanism and a quantization strategy aiming at multi-channel random spoofing attack according to the state space equation established in the step S1;
s3, establishing a closed-loop control system of the single-arm manipulator according to the asynchronous output feedback controller designed in the S2; based on Lyapunov theory, establishing sufficient conditions for ensuring random stability and strict dissipation performance of a closed-loop control system of a single-arm manipulator, and solving a controller gain matrix;
s4, substituting the controller gain matrix obtained in the step S3 into an asynchronous output feedback controller, and controlling the output angle and the output angular speed of the single-arm manipulator by using the asynchronous output feedback controller under multi-channel attack, so that a closed-loop control system of the single-arm manipulator is randomly stable, and strict dissipation performance is met;
the method for establishing the state space equation obeying the Markov jump in the step S1 is specifically as follows:
according to the mechanical model of the single-arm manipulator, a dynamic equation of the single-arm manipulator is established as follows:
wherein θ is the output angle, Q is the moment of inertia, D (t) is the viscous coefficient of friction of the joint rotation, mglsin (θ) is the gravitational term of the single link mechanical arm, u is the control moment of the single link mechanical arm, M is the mass of the payload, g is the gravitational acceleration, and l is the length of the arm;
selecting x 1 (t) =θ is the output angle of the single arm manipulator,for outputting the angular velocity and satisfy +.>
Selecting x (t) as a system state, y (t) as an output position signal, u (t) as a control input, and ω (t) as external disturbance, and then the single-arm manipulator state equation is:
wherein x (t), A, B, C, D, D 0 The definition is as follows:
further, after considering the measurement output of the system, the state space equation obeying the Markov jump can be obtained as follows:
wherein z (t) is the measurement output; lambda (t), t>0 denotes a Markov process defined on a complete probability space, in a finite setIn the middle value, transition probability matrix->The transition probability is as follows:
wherein, when Deltat is more than or equal to 0,ρ αl the transfer rate of the system from the alpha mode at time t to the l mode at time t+delta t is shown by +.>
The step S2 designs an asynchronous output feedback controller based on a dynamic event trigger mechanism and a quantization strategy aiming at the multichannel random spoofing attack, and the specific method is as follows:
the dynamic event triggering mechanism is designed as follows:
wherein,y(t k h)、kh、t k h is the transmitted sampling data, sampling time and latest triggering time respectively; j (J) 1 (λ(t))>0，J 2 (λ(t))>0 is a modal dependent weight matrix, v>0 is a given constant, δ (λ (t))e (0, 1) is a given modality dependent threshold parameter; the internal dynamic variable η (t) satisfies: />And eta (t) 0 )＝η 0 ≥0；
In addition, since the communication channel has a limited bandwidth, the transmitted signal is quantized by the quantizer, so that the transmission load of the signal is reduced, and the output signal released by the dynamic event trigger mechanism in step S2, i.e., the sampled data y (t k h) The logarithmic quantizer used for quantization is:
wherein,for any quantization error, the quantized output expression is obtained by a sector boundary method as follows:
wherein,
definition of the definition
Using multi-channel transmission strategy, and considering that each transmission channel may be attacked by different network, a HMM-based transmission schedulerf t Representing the total number of transmission channels, the scheduler pi (t) satisfies a pre-known conditional probability matrix +.>Expressed as:
wherein,and->Based on the modal information of the system, at each transmission moment, the scheduler only selects one channel to transmit data;
in network communication, a spoofing attack often occurs, an attack signal is injected into a channel between a sensor and a controller to replace original signal information, and assuming that an attacker can capture system dynamics and release an aggressive signal in a random manner, system information acquired by the controller under the influence of the attack signal is as follows:
the asynchronous output feedback controller based on the HMM is as follows:
u(t)＝K v {q(y(t k h))+β r (t)[-q(y(t k h))+a r (y(t))]} (10)
wherein K is v For the controller gain matrix, beta r (t) ∈ {0,1} represents Bernoulli procedure for characterizing whether or not a spoofing attack occurs at time t, a r (y (t)) represents attack signals released in a random manner, q (y (t) k h) Representing captured system dynamics, and in addition, ρ (t), t.gtoreq.0 is a Markov process, satisfying a conditional probability matrixAnd conditional probabilities are described as follows:
wherein,
substituting (10) into (3) to obtain a closed-loop control system of the single-arm manipulator containing Markov jump under the multi-channel attack of dynamic event triggering and quantification, wherein the closed-loop control system comprises the following steps:
the random stability of the design single arm manipulator mentioned in step S3 is as follows:
this condition is satisfied, then the closed-loop control system is randomly stable when ω (t) ≡0;
likewise, the designed single arm robot dissipation performance mentioned in step S3 is as follows:
if the condition is met, the closed loop control system meets strict dissipation performance;
wherein J (z (t), ω (t))=z T ψ 1 z(t)+2z T ψ 2 ω(t)+ω T (t)ψ 3 ω(t)，ψ 1 、ψ 2 、ψ 3 And gamma is a dissipation performance index as a real matrix.
2. The method for controlling dynamic event triggering and quantization of a single-arm manipulator under multi-channel attack according to claim 1, wherein based on lyapunov theory, a sufficient condition for ensuring random stability of a closed-loop control system of a Markov jump single-arm manipulator and meeting strict dissipation is established, and a controller gain is solved by adopting an LMI tool kit of MATLAB, and the method comprises the following specific steps:
based on lyapunov theory, sufficient conditions to ensure random stability of the closed loop control system and meet stringent dissipation performance are as follows:
for a given parameter τ M >0，δ α ∈[0,1)，And real matrix-> If matrix P is present α >0,R>0,Q>0,H>0,J 1α >0,J 2α >0,W avr >0, N, Y, for any ofSo that the formulas (14), (15) and (16) are established:
wherein,
the closed loop control system is randomly stable and meets the strict dissipation performance;
according to the inequality of the linear matrix, the controller gain is solved as follows:
for a given parameter τ M >0,δ α ∈[0,1),Sum-real matrixIf matrix P is present α >0,R>0,Q>0,H>0,J 1α >0,J 2α >0,W avr >0,N,Y,Z υ ,χ υ Parameter epsilon>0, for arbitrary->So that inequality equation (14), equation (15) and the following equation hold:
wherein the method comprises the steps of
The controller gain matrix may be:
the closed loop control system is randomly stable and meets the stringent dissipation performance.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6473772B1 (en) * | 1998-12-17 | 2002-10-29 | International Business Machines Corporation | Apparatus and methods for dynamic simulation event triggering |
| CN110865616A (en) * | 2019-11-07 | 2020-03-06 | 河南农业大学 | Design method of event trigger zone memory DOF controller under random FDI attack |
| CN111673750A (en) * | 2020-06-12 | 2020-09-18 | 南京邮电大学 | Speed synchronization control scheme of master-slave type multi-mechanical arm system under deception attack |
| CN113325822A (en) * | 2021-05-25 | 2021-08-31 | 四川大学 | Network control system fault detection method based on dynamic event trigger mechanism and sensor nonlinearity |
| CN115755623A (en) * | 2022-12-13 | 2023-03-07 | 南京工业大学 | Fault tolerance control method based on event-triggered intermediate observer |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6473772B1 (en) * | 1998-12-17 | 2002-10-29 | International Business Machines Corporation | Apparatus and methods for dynamic simulation event triggering |
| CN110865616A (en) * | 2019-11-07 | 2020-03-06 | 河南农业大学 | Design method of event trigger zone memory DOF controller under random FDI attack |
| CN111673750A (en) * | 2020-06-12 | 2020-09-18 | 南京邮电大学 | Speed synchronization control scheme of master-slave type multi-mechanical arm system under deception attack |
| CN113325822A (en) * | 2021-05-25 | 2021-08-31 | 四川大学 | Network control system fault detection method based on dynamic event trigger mechanism and sensor nonlinearity |
| CN115755623A (en) * | 2022-12-13 | 2023-03-07 | 南京工业大学 | Fault tolerance control method based on event-triggered intermediate observer |
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