11 results about "Exponential stability" patented technology

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 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 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 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 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 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.