International Journal of Robust and Nonlinear Control最新文献

This article investigates the stochastic stability of stochastic differential delay systems (SDDSs) with path information and their applications in consensus control of multi-agent systems (MASs) based on the path information feedback. Here, the integral path information and fragment-integral path information are considered, respectively. The mean square (m.s.) and almost sure (a.s.) exponential stability criteria of the SDDSs with path integral information are established respectively according to the two types of path information. It is shown that the fragment-integral term may work positively for stochastic stability. Moreover, the obtained stochastic stability theorems are applied to design a distributed proportional integral/fragment-integral control protocol and establish consensus conditions for stochastic MASs under proportional-integral (PI)-type controls. Finally, the effectiveness of the results is verified through two simulation examples.

This article explores a decision-making problem with partial information in a multi-coalition game that involves both cooperation and competition. Considering heterogeneous players with general linear systems, we propose a distributed algorithm that employs average consensus mechanisms to estimate the gradient of the coalition function among players within each coalition and utilizes leader-following protocols to estimate the actions of all players across multiple coalitions. Furthermore, to reduce communication costs, a dynamic event-triggered mechanism (ETM) is introduced into the average consensus and leader-following protocols. The ETM is asynchronous, eliminating the requirement for a global clock and allowing players to transmit information only when the triggering condition is satisfied. By the Lyapunov analysis, all actions asymptotically converge to the Nash equilibrium by the proposed algorithms. Moreover, the unmanned surface vehicle (USV) swarm confrontation is formulated as a coalition game. In the scenario of safeguarding territorial integrity, we devise specific tasks for both the invading and defending USVs, encompassing elements such as formation, intrusion, defense, and so forth. The effectiveness of the proposed algorithms is validated through comprehensive simulations.

In the context of the increasing security issues of cyber-physical systems (CPSs), this paper addresses the parameter identification of binary observation-based finite impulse response (FIR) systems under replay attacks, overcoming the problem of high nonlinearity of quantized systems and greater data sparsity caused by replay attacks. For the attacker, based on the energy-constrained condition, an optimization attack model is established to maximize the absolute error of identification, giving the method of obtaining the optimal attack strategy. Following the defender, the identifiability of unknown parameters is discussed and a robust defense scheme is proposed. This scheme involves a joint identification strategy for both the attack strategy and unknown parameters. By enhancing the excitability of system inputs, consistent identification is ensured despite replay attacks. An algorithm for the accomplishment of the joint identification strategy is presented based on the grid search method. Rationality of the method is confirmed with performing numerical simulations.

The fault estimation and fault-tolerant control problems of switching stochastic systems with partially unknown nonlinear dynamics, external disturbance, actuator, and sensor faults are studied. A new observer and disturbance observer are constructed to simultaneously estimate the system state, actuator, and sensor faults, as well as modelable disturbances. The dimensions of the proposed adjustable dimension observer are not fixed and can be adjusted within a certain range, and unknown nonlinear dynamics can be decoupled. According to estimated information, fault-tolerant controller is designed. The sufficient condition is obtained to ensure that the root-mean-square gain from the disturbances to the fault reconstruction error is bounded. Finally, two simulation examples are provided to verify the effectiveness of the proposed method.

In the context of model-based fault detection, it is crucial to achieve strong robustness against disturbance and noise. However, the existing robust fault detection methods typically address disturbance and noise in a centralized manner to enhance robustness, which may cause some conservatism since the dynamic characteristics of disturbance and noise are considerably different. In addition, most of the existing model-based fault detection method is implemented with constant thresholds, which may further introduce conservatism. In this context, this paper proposes a guaranteed disturbance compensation and robust fault detection method based on zonotopic evaluation for the discrete-time systems subject to unknown but bounded disturbance and noise. To this end, a disturbance compensation controller is developed based on $��{�L�}_{�\infty �}�$ technology to obtain guaranteed control performance. Moreover, the control performances with or without disturbance compensation are analyzed based on zonotopes. By considering the disturbance dynamic characteristics, an extended fault detection observer (EFDO) is created to pursue robustness to disturbance, noise, and sensitivity to fault simultaneously. Meanwhile, a multi-objective EFDO is devised by exploiting the $��{�L�}_{�\infty �}�$ index and $��{�H�}_{�-�}�$ index as the criteria within the finite-frequency domain. Furthermore, the zonotopic residual evaluation is further deployed to generate the residual boundary, which helps to reduce the conservatism of fault detection. The superiority of the proposed method is theoretically analyzed. Simulation results also validate the effectiveness and superiority of the proposed method in disturbance compensation fault detection.

This study proposes a fault estimation and tolerant anti-disturbance switching control (ADSC) approach for the switched systems subject to the system fault and multiple disturbances. The fault dose not required to have a model. The disturbances contain the modeled unmeasurable part and the unmodeled measurable part. First, a composite switching estimator is constructed to simultaneously estimate the unavailable system state, fault and modeled disturbance. Then, by means of the estimator, a switching controller is developed to tolerant the fault and complement the modeled disturbance. Further, under the average dwell time relevant switching signals, criteria are established to ensure the fault estimation performance and robustness property for the switched systems. Finally, via implementing the presented fault estimation and tolerant ADSC scheme on a switched circuit system to regulate the charge and flux, the reasonability of the established result is verified.

The fixed-time robust neural learning control for nonlinear strict-feedback systems with output constraint and unknown dynamics is investigated in this article. The system nonlinearity is identified using neural network (NN) while the prescribed performance design is employed to avoid the output constraint to be violated. Considering the intelligent approximator only working in an active domain, the smooth switching mechanism is introduced to indicate its effectiveness. Based on the designs of neural approximation and switching signal, a robust adaptive controller is constructed where the NN works in the active domain and the fixed-time robust design works outside of that domain. Especially for the neural update law, the estimation error is constructed based on a state observer and a serial-parallel identification system, even though the real system nonlinearity is not available. The effective neural approximation is achieved while the error signals are ensured to be practical fixed-time stable. Simulation tests are ultimately conducted to demonstrate the validity of the design.

A robust unknown input observer (UIO) is designed for nonlinear quadratic systems (NQSs) affected by unknown input, disturbance, and noise. It is assumed that in this article the system states and their estimates are varying inside a hyper-rectangle region of known vertices. Based upon satisfying the observer matching condition and the minimum phase condition (at every vertex of the hyper-rectangle region of the system states and their estimates), a set of tractable linear matrix inequalities (LMIs) is derived for computing the design matrices of robust UIO. The design methodology of robust UIO is extended to NQSs affected by sensor fault, disturbance, and noise. By modeling the sensor fault as a system state with unknown sensor fault input, it is found that the observer matching condition is satisfied and only the minimum phase condition should be verified at every vertex of the hyper-rectangle region of the system states and their estimates. Another set of tractable LMIs is derived to compute the design matrices of robust UIO, which simultaneously estimates the system's states and sensor faults. A practical example of a nonlinear quadratic Rössler circuit affected by sensor fault, disturbance, and noise is used to show the design steps and to verify the proposed robust UIO. Simulation results indicate the ability of the proposed robust UIO to simultaneously estimate the system's states and sensor faults of NQSs affected by disturbance and noise.

This article focuses on the pth moment exponential stability of discrete-time Markov switched stochastic systems with state-dependent delay. By using Razumikhin technique, and stochastic analysis techniques, the state-dependent delay with randomness due to the randomness of the system state can be addressed. With the help of stationary distribution of Markov switching and multiple Lyapunov–Krasovskii functionals approach, an appropriate switching rule is designed and a novel theorem on discrete-time Markov switched stochastic systems with state-dependent delay is established. Different from the previous results, the Markov switched with partially unstable subsystems and the state-dependent delay with randomness are considered in this article, which brings many differences to the stability analysis of the system compared to traditional stability analysis. Furthermore, an illustrative example is performed to illustrate the effectiveness of the main theory.