28 results about "Exponential stability" patented technology

The invention relates to the technical field of network detection, and provides a dynamic event trigger fault detection method under DoS network attack, which comprises the following steps: establishing a linear state space model of a network control system; defining a non-attack interval and an attack interval of system operation, and constraining attack frequency and duration; the observer gain is switched according to the current non-attack interval or attack interval of the system; a dynamic event triggering mechanism is constructed, and the triggering condition depends on the output state and the internal dynamic variable of the full-order switching observer and is used for dynamically adjusting the data transmission frequency; establishing a closed-loop switching system model; and analyzing system index stability according to the closed-loop switching system model, and cooperatively designing observer gain, controller gain and event triggering parameters. According to the invention, through quantification of the DoS attack model, the dynamic event triggering mechanism and collaborative optimization design, the effects of effectively detecting the system fault and improving the utilization rate of the network channel are achieved.

The invention relates to the field of safety control of a networked control system with communication constraints, in particular to a sampling controller design method based on state feedback of a networked control system. Comprising the following steps: constructing a random integral quadratic constraint operator on the basis of a networked control system based on an uncertain disturbance model to quantify uncertainty caused by sampling interval and false data injection attack and data packet loss; model transformation is carried out, and corresponding index stability conditions are given for a closed-loop system; analyzing the H-infinity performance index of the closed-loop system by using a random integral quadratic constraint operator and a KYP lemma; a two-stage heuristic solving iterative algorithm based on the state feedback controller is designed; the reliability and feasibility of the controller are verified through numerical simulation. The challenge brought by combination of false data injection attack and data packet loss is specifically solved.

This invention discloses an asynchronous, non-fragile H∞ control method and system for a rotating inverted pendulum, belonging to the field of robust control technology for DC motor rotating inverted pendulums. Addressing the problems of modal asynchrony, controller gain perturbation, time-varying delay, and quantization error in DC motor rotating inverted pendulum systems, this invention proposes an asynchronous, non-fragile H∞ control framework. The main steps include: constructing a Markov jump singular perturbation system model with time-varying delay and variable quantization density; designing an asynchronous, non-fragile output feedback controller for the rotating inverted pendulum, compatible with controller gain perturbation and quantization uncertainty; and deriving the linear matrix inequality conditions through modal-dependent Lyapunov functions to ensure the system's exponential stability in finite time and to meet the preset H∞ performance index. This invention can effectively improve the robustness and stability of DC motor rotating inverted pendulums under attack and parameter perturbation scenarios.

The invention discloses an industrial robotic arm control method and system based on time-varying time-delay neural network index stability, and the method comprises the steps: collecting the position, speed and acceleration of each joint of an industrial robotic arm, and constructing a time-delay term-containing dynamic model through a system identification algorithm; a time-varying and time-delay industrial robotic arm control neural network is constructed, an input layer receives state and time-delay information, a hidden layer has neurons with time-varying and time-delay characteristics, and an output layer outputs an estimated value of the uncertainty of a dynamic model. Based on the Lyapunov stability theory, in combination with an expected trajectory generation algorithm, position and speed tracking errors are calculated, a control law based on exponential stability is designed, and a neural network parameter updating algorithm is designed by using a Lyapunov function. According to the method, the dynamic characteristics of the robotic arm can be described more accurately, the control precision and stability are improved, the adaptability of the robotic arm to complex working conditions is enhanced, and a reliable basis is provided for subsequent control design.

The invention discloses a cross-layer elastic control method for a networked switching system based on reinforcement learning, and belongs to the technical field of networked system safety control. In a network layer, a confrontation interaction relationship between a defending party and an attacking party is described by constructing a constraint zero-sum game model, and a constraint condition is determined by solvability of an algebraic Riccati equation of a physical layer. Based on the model, a closed-loop explicit solution for constraining Nash equilibrium is deduced, and the equilibrium packet loss rate required by the design of each subsystem controller is determined according to the closed-loop explicit solution. In order to solve the problem of open-loop operation and modal asynchronization caused by denial of service attack, a slow switching mechanism based on residence time is adopted, and the mean square index stability of the system can be ensured without parameter setting. Modeling an optimal switching signal selection problem as a Markov decision process in a hybrid state space; the invention further provides an improved deep Q network algorithm which is used for solving the Markov decision process, and the dynamic performance of the system is effectively improved while the residence time constraint is met.

The application discloses a dynamic self-triggering filtering method under incomplete semi-Markov kernel information, relates to the technical field of automatic control and signal processing, and aims at the problems of difficult acquisition of semi-Markov kernel information, heavy communication burden and insufficient peak value control. The semi-Markov information known / unknown set is classified, the known parameters and the lower bound are utilized, a self-triggering mechanism containing dynamic variables is designed to determine the data transmission time, a modal dependent filter is constructed, the Lyapunov theory and the linear matrix inequality technology are combined to verify the mean square exponential stability and the robust performance of the filtering error system, and the problems of high conservativeness and resource waste of the existing method are solved.

The application discloses a boundary control and output regulation method for a flexible gantry crane system. The application comprises the following steps: based on a non-disturbance system, a preliminary state feedback controller is designed by using the boundary state of the system; based on the preliminary controller, the existence of an ISS-Lyapunov function is proved; based on the existence of the ISS-Lyapunov function, an integral regulation term is added to the preliminary controller; a new Lyapunov function is constructed by using a feedforward method; the well-posedness of the obtained closed-loop system is analyzed by using the Lumer-Phillips theorem, and the exponential stability of the closed-loop system is proved; the above analysis is extended to a system containing disturbance, and the output regulation problem is solved; the application can reduce the complexity of implementation while improving the control performance of the system, realizing accurate output regulation and system stability, and better adapting to the requirements of the actual working environment.

The invention provides a buffeting-free sliding mode control method and device with pulse random disturbance, electronic equipment and a readable storage medium. The method comprises the following steps: firstly, establishing a dynamic model of a pulse random time delay system with bounded state time delay and uncertainty; a sliding mode surface is designed for the dynamic model, so that the system meets the expected stability once reaching the sliding mode surface; determining a sliding mode dynamic equation based on a sliding mode surface in combination with the dynamic model; based on the sliding mode equation, obtaining a judgment condition and a sliding mode surface parameter matrix for ensuring the index stability under the dynamic mean square significance of the sliding mode; and introducing a hyperbolic tangent function as continuous smooth approximation of a switching function, and constructing a buffeting-free sliding mode controller by using a sliding mode surface parameter matrix to realize control of a pulse random time delay system. By using the sliding mode control method, the problem that the sliding mode control precision is low due to the fact that an existing sliding mode control method cannot process pulses, environmental noise, time lag and uncertainty at the same time and the influence of external disturbance on the controlled output of the system is large can be solved.

The invention discloses an anti-DoS attack iterative learning robust prediction control method for an intermittent reaction kettle. The method comprises the following steps: step 1, establishing a state space model of a low-time-delay intermittent reaction kettle suffering from DoS attack; 2, converting the constructed state space model of the low-time-lag intermittent reaction kettle subjected to DoS attack into an expanded state space model; 3, designing an iterative learning robust elastic predictive control law; step 4, providing an index stability condition of the system based on a modal-dependent average residence time method; step 5, combining the robust positive definite invariant set and the terminal constraint set to give a sufficient condition for ensuring the stability of the system; 6, solving the control law gain and the longest duration of the DoS attack; according to the method, the problem of prediction error accumulation of a traditional method can be effectively solved, the maximum attack duration is estimated through the mode-dependent average residence time method, the optimal control sequence length is determined accordingly, and communication resource consumption is balanced on the premise that the stability of a closed loop is guaranteed.

The invention belongs to the technical field of vehicle active suspension control, and provides an active suspension event trigger control method and system based on a high-order all-wheel-drive system, an active suspension system is modeled into a four-order system, which is beneficial to direct synthesis of a control law of an expected tracking error dynamic state, and communication resources in a network control system are saved. A fixed threshold event triggering mechanism is adopted, and a hyperbolic tangent function is introduced to ensure the exponential stability of a controlled system. In addition, uncertainty and interference in an actual system can seriously affect the vibration isolation performance of a suspension system. Therefore, a universal dynamic compensator is designed to better suppress unknown interference. And finally, stability analysis is carried out on the uncertain nonlinear suspension system, effective vibration isolation control of the active suspension system is realized, the communication burden is reduced, the smoothness is improved, and the engineering applicability is enhanced.

The present application belongs to the technical field of adaptive control of thermoacoustic oscillation system, and discloses an adaptive control method for a thermoacoustic oscillation system with unknown input time delay. Through an adaptive backstepping control method, the exponential stability of a Rijke tube system can be ensured even in the case that the actuator time delay is unknown and time-varying, and the system instability problem caused by the fact that the existing control method does not consider the time delay or the time delay is unknown is solved. Full-state feedback control can be realized by measuring only part of the boundary information such as the sound pressure at the upper end of the tube and the sound velocity at the lower end, the sensor configuration cost and the system complexity are reduced, and the method is more suitable for engineering practice. Through adaptive time delay estimation and projection operator mechanism, the controller has good robustness to time delay variation and model uncertainty, and can quickly converge to the true time delay under different initial estimation values without affecting the system stability. The present application provides a new way for the stable control of an aero-engine combustion system.

The invention belongs to the technical field of self-adaptive control of a thermoacoustic oscillation system, and discloses a self-adaptive control method of a thermoacoustic oscillation system with unknown input time delay. Through the self-adaptive backstepping control method, the index stability of the Rijke management system can still be ensured even under the condition that the time delay of an actuator is unknown and varies, and the problem of system instability caused by the fact that an existing control method does not consider the time delay or the time delay is unknown is solved; full-state feedback control can be achieved only by measuring part of boundary information such as the upper end sound pressure and the lower end sound velocity of the pipe, the sensor configuration cost and the system complexity are reduced, and the method is more suitable for engineering practice; through adaptive time delay estimation and a projection operator mechanism, a controller has good robustness for time delay change and model uncertainty, real time delay can be quickly converged under different initial estimation values, and the system stability is not affected; and a new way is provided for stable control of an aero-engine combustion system.

The present invention belongs to the field of information security technology, and particularly relates to a fusion filtering method for unmanned surface vessels with sensor saturation under FDI attacks. A discrete-time multi-sensor network system model is constructed, and a real matrix inequality is constructed based on linear and non-linear functions to optimize the filter design, and the filter is made to exhibit exponential stability in the mean square sense; according to the local filter parameters, a distributed fusion filter is designed to resist FDI attacks. By using the optimized design and distributed strategy, the anti-interference ability and data fusion accuracy of unmanned surface vessels in harsh environments are improved.

The present invention provides a modelling and H∞ control method for two-phase annular flow in an oil and gas transport system. The method includes: establishing a model of two-phase annular flow based on the two-dimensional Kuramoto-Sivashinsky equation; projecting the system onto the eigenspace of the two-dimensional Sturm-Liouville operator using modal decomposition; establishing the closed-loop system and deriving the sufficient condition for internal exponential stability and the satisfaction of given performance criteria using the direct Lyapunov method, thereby solving the H∞ control problem for the Kuramoto-Sivashinsky system. The advantages of this invention include: simpler implementation for practical engineering, less implementation devices, and effective suppression and robustness against external disturbances.

The invention belongs to the field of control science and engineering, and particularly discloses a stability analysis and control method and system for a discrete time network control system, and the method comprises the following steps: dividing a time delay interval of the system into a plurality of time delay sub-intervals which are not intersected, and enabling each sub-interval to correspond to a time delay mode, the time delay mode comprises a stable mode and an unstable mode; constructing a discrete time switching system model composed of a plurality of modes, designing a corresponding state feedback controller gain for each time delay mode, and designing a mode-related variable gain controller; in combination with a modal average residence time condition and multi-Lyapunov function construction, an exponential stability criterion capable of processing an unstable modal and a controller design method are provided. The method provided by the invention can effectively reduce the analysis conservative property, improves the robustness and dynamic performance of the system, and is suitable for time delay system control in a complex network environment.

The invention belongs to the field of control algorithm design, and discloses a data-driven model predictive control design and a stability analysis method thereof. For a linear time-invariant system, a prediction model is constructed by using input and output data in a data driving mode, and system parameter identification is not needed. Wherein iterative updating of model parameters is realized in combination with a recursive least square technology, and adaptive control of a complex nonlinear system is realized in combination with subspace identification and model prediction control. Then, by constructing a Lyapunov function, the closed-loop exponential stability of the data-driven model prediction control method is theoretically proved. Compared with standard subspace prediction control, the method has smaller tracking errors and overshoot, and stability and accuracy are remarkably improved. Therefore, the prediction model can be updated online without a prior model, and the adaptability is high; stability is strictly proved, and the method is suitable for systems with high safety requirements. And the aero-engine verifies that the method shows excellent engineering practicability.

The invention discloses a model-free adaptive control method for a motorcade under trust mapping-driven hybrid attacks. The method comprises the following steps of: 1, processing a vehicle state and communication characteristics by utilizing a multi-layer perceptron, outputting a continuous trust value, mapping the continuous trust value into a weight factor through a cumulative distribution function, and correcting an expected distance and a control law in real time; 2, designing a distributed control law based on the expected distance and the relative state error, and constructing an equivalent data model based on input and output data under a model-free adaptive control framework; establishing an exponential stability and serial stability criterion by using a functional and linear matrix inequality, and solving a control gain; and 3, realizing real-time robust suppression and smooth recovery of various attacks of false data injection, replay, camouflage and denial of service by cyclically executing the first two steps. According to the method, the speed consistency and the rapid convergence of the spacing error can be realized in a mixed attack environment, and the robustness and the engineering implementation of fleet control are remarkably improved.

The invention provides a security reinforcement learning control method and system for an average residence time switching system based on multiple Lyapunov stability constraints, and belongs to the field of intelligent control and reinforcement learning. The objective of the invention is to solve the problem of how to introduce a multi-Lyapunov stability criterion suitable for a switching system in reinforcement learning and realize stable and reliable strategy learning on the premise of satisfying an average residence time constraint. According to the method, a mode-dependent Lyapunov function is constructed for each subsystem mode, a multi-Lyapunov stability criterion meeting an average residence time condition is introduced, and a multi-Lyapunov descent constraint is explicitly applied in a reinforcement learning strategy updating process; therefore, the mean square index stability of the switching system in the learning stage and the execution stage is realized. The method does not need to depend on an accurate system dynamics model, can safely learn a mode-dependent control strategy only based on the state and control data collected in the system operation process, and has high robustness and engineering applicability.

The invention discloses a passive fault-tolerant control method for an active suspension system under an actuator fault. The method comprises the following steps: constructing an NPV model containing a time-varying actuator fault; constructing a vehicle active suspension system model based on an NPV frame; modeling according to the actuator fault on the basis of the vehicle active suspension system model to obtain an active suspension model containing the time-varying actuator fault; an exponential stabilization passive fault-tolerant controller based on a nonlinear variable parameter framework is designed in combination with input limitation, so that a fault system reaches global consistent exponential stability at an original point, and the fault system meets input constraint conditions in an initial state; a hybrid stable passive fault-tolerant controller based on a nonlinear variable parameter frame is designed in combination with a finite time theory, and vehicle control is realized in combination with an active suspension model containing a time-varying actuator fault. The steady-state and dynamic performance of the suspension system is optimized, the stability and riding comfort of a vehicle body are ensured, and the safety and riding experience are remarkably improved.

This invention discloses a secure binary synchronization method for coupled neural networks based on average quasi-periodic intermittent control. By constructing a coupled neural network model comprising a target network and multiple follower networks, an error model between the follower and target networks is defined. Deception attack and random disturbance models are established for the intermittent control and non-control intervals, respectively. Using hybrid system theory, stochastic Lyapunov stability theory, and matrix inequality techniques, sufficient conditions for ensuring the mean-square exponential stability of the error system are derived. An aperiodic intermittent security controller is designed, which, by adjusting the control gain parameter and control interval, ensures the mean-square bounded stability of the error system, achieving secure binary synchronization of the coupled neural network. This method improves the control resilience and adaptability of the network under attacks and disturbances, and is applicable to distributed collaborative and secure control scenarios such as smart grids and sensor networks.

The present invention discloses a non-periodic sampling data H-infinity control method for an automotive active suspension system based on an uncertain discrete-time model. The present invention relates to the non-periodic sampling data H-infinity control problem of an uncertain discrete-time model and an automotive active suspension system with time-varying time delay. The steps of the present invention are as follows: Step 1: Discretize the system by using a lifting technique, and quantify the uncertainties caused by sampling data and delay by finding the integral quadratic constraint multiplier; Step 2: Through model transformation, give the conditions for the exponential stability of the closed-loop system, and use the KYP lemma to transform it into an LMI condition; Step 3: Utilize the energy function of the uncertainty operator and the integral quadratic constraint characteristics to optimize the H-infinity performance measurement ride comfort; Step 4: Design an algorithm for obtaining the controller gain; Step 5: Take a four-section vehicle model as an example to verify the effectiveness and optimization effect of the method. The present invention is used in the field of automotive active suspension control.

The application belongs to the field of unmanned system cluster control and autonomous cooperation, and particularly relates to an unmanned system cluster acceleration synchronization method for multi-channel network interruption. A kind of unmanned aerial vehicle cluster system is modeled as a linear system model, and a multi-channel communication topology network and a distributed elastic controller of the unmanned aerial vehicle cluster system are constructed for the model. A Lyapunov function depending on the network interruption mode is constructed, and the exponential stability and gain conditions of the synchronization error system under different network interruption modes are established to cope with the synchronization error. The synchronization rate is characterized as an optimization problem characterized by single-channel attenuation rate and network interruption duration constraints. Then, an iterative optimization algorithm is designed to solve the controller gain under different network interruption modes to achieve accelerated synchronization. Finally, the proposed method is simulated and verified, and the results show that the method can effectively solve the problem of accelerated synchronization of unmanned system cluster under multi-channel network interruption.

The application discloses a kind of distributed leakage estimation method of urban drainage pipe network based on sensor network.The method constructs the topological structure of sensor network and the state space model of urban drainage pipe network, describes the nonlinear random variation in drainage pipe network by using Bernoulli random sequence, describes the measurement attenuation phenomenon randomly occurred when sensor measures by using Rice attenuation model, and adopts Round-Robin communication protocol for data transmission scheduling;Then design distributed state estimator, then establish error augmented system, obtain the sufficient condition of mean square exponential stability and H ∞ performance;Finally, the gain matrix of distributed estimator is obtained by convex optimization method.It provides a real-time and effective method for accurate remote estimation and monitoring of urban drainage pipe network.

This invention discloses a nonlinear multi-agent exponential consistency sliding mode control method, relating to the field of multi-agent system cooperative control technology, including: S1, constructing a nonlinear multi-agent system model, defining tracking error and exponential consistency of moment order; S2, constructing an integral sliding surface and deriving the equivalent control law; S3, constructing a Lyapunov-Krasovsky functional, analyzing the exponential stability of the p-th moment order, and designing a finite-time reachable sliding mode controller; S4, initializing parameters, acquiring the state of the nonlinear multi-agent system model in real time and calculating the tracking error, calculating the control input and applying the result to the nonlinear multi-agent model to complete rolling optimization control; the nonlinear multi-agent exponential consistency sliding mode control method provided by this invention solves the exponential consistency control problem of multi-agent systems under complex disturbances, time-varying time delays, and topology jumps, improving the robustness and convergence performance of the system.

The invention provides a rapid consistency control method for an aircraft cluster under unreliable communication, and belongs to the technical field of cooperative control of aircraft clusters. Comprising the following steps: modeling an aircraft motion control system into a linear system model, and constructing a communication topology network and a distributed state feedback controller between aircraft clusters for the model; a new time-varying Lyapunov function based on the switching topology is designed, and a sufficient condition presented in a linear matrix inequality form is established based on the function so as to ensure that the consistency error system realizes exponential stability under the unreliable communication topology. According to the invention, an SCD optimization algorithm is designed to solve the controller gain so as to realize the optimal convergence rate. And finally, simulation verification is carried out on the proposed method by adopting a linearized longitudinal dynamic model of the aircraft, and the result shows that the consistency control problem of the aircraft cluster under the unreliable communication topology can be effectively solved, and the optimal convergence rate is realized.

The invention provides an almost inevitable exponential stability analysis method of a nonlinear random system with random pulses and application of the almost inevitable exponential stability analysis method in chaotic synchronization. The almost inevitable exponential stability analysis method comprises the following steps: establishing a mathematical model of a pulse random system influenced by random noise and random pulses; a Lyapunov method is used to provide a new almost inevitable index stability condition of a pulse random system driven by an updating process and a Markov chain under different conditions. The invention provides an analysis method capable of comprehensively considering random pulse intensity and density randomness, establishing a stability criterion suitable for random pulse control, and applying the stability criterion to a synchronization problem of a master-slave random chaotic system.

The present invention designs a Rijke tube thermoacoustic instability boundary proportional control method; establishes a Rijke tube PDE model of a cascade of heat release model and gas dynamic equation; proposes boundary proportional control using the upper end pressure and lower end sound velocity of the Rijke tube as outputs to make the thermoacoustic unstable system exponentially stable; compared with the backstepping control method, it selects a feedback quantity that is easier to measure rather than full-state measurement, and chooses proportional control that is easy to implement, which brings convenience to practical application; theoretically, it strictly provides sufficient conditions to ensure the exponential stability of the system, and converts the conditions into sufficient and necessary conditions that are easier to solve; for the boundary feedback control parameter optimization problem when the system exponential stability decays fastest, the above conditions are converted into a nonlinear programming problem for solution, and the optimal design scheme of the control parameters is provided. The boundary proportional control method for the thermoacoustic instability phenomenon in the combustion chamber proposed by the present invention is feasible and effective, and can meet the requirements of suppressing the thermoacoustic instability phenomenon.

The application discloses a nonlinear discrete generalized switching system control method with edge-dependent average dwell time, a system and a storage medium, relates to the technical field of switching system control, and aims at solving the problems that the existing method models a switching signal as having average dwell time or mode-dependent average dwell time, ignores the edge-dependent characteristics of the switching signal, causes the controller design to be conservative when facing a switching system with a directed dwell time characteristic, and reduces system stabilizability and closed-loop system performance. The application comprises the following steps: step one, constructing a discrete nonlinear generalized switching system state space expression with edge-dependent average dwell time; step two, giving a condition for the existence of a unique solution of an open-loop system of the discrete nonlinear generalized switching system; step three, giving a dwell time condition for the open-loop system of the discrete nonlinear generalized switching system to meet exponential stability; and step four, selecting a system performance index and designing a controller of a closed-loop system.