International Journal of Robust and Nonlinear Control最新文献

The sliding mode control (SMC) strategy based on genetic algorithm is proposed for discrete two-dimensional (2-D) Markov switching systems with the Roesser model. By means of common 2-D sliding surface, the 2-D SMC law is designed for the underlying system. According to Lyapunov stability criteria, sufficient conditions are established for the asymptotic mean-square stability of the underlying 2-D Markov switching systems and the reachability of the sliding region is guaranteed. Utilizing an iteration optimizing algorithm, an effective SMC strategy under genetic algorithm is constructed to minimize the sliding region by searching an ideal sliding gain. Finally, the applicability of the proposed 2-D SMC strategy is verified through an example.

In this article, a new predictor-based anti-disturbance control scheme is proposed for discrete-time systems with input delay subject to time-varying uncertainties, by only using the system output measurement. A high-order extended state observer is firstly constructed to simultaneously estimate the system state, unknown disturbance and its high-order difference with specification. Two alternative designs of the system state and disturbance predictors are then presented to construct an advanced anti-disturbance control scheme. The disturbance attenuation performance of the resulting closed-loop system is quantitatively analyzed. Moreover, a matrix-inequality-based sufficient condition is established to evaluate robust stability of the closed-loop system under time-varying uncertainties. Finally, a benchmark example is adopted to demonstrate the effectiveness and advantages of the proposed control schemes over the existing methods.

The influence of analog fading channels on platoon control performance is studied via relative output feedback. The main goal is to determine the existence of a distributed output feedback controller capable of achieving mean square stability (MSS) for the underlying vehicle platoon systems over analog fading channels. First, the conditions, closely associated with the statistical characteristics of fading channels, for achieving platoon MSS are derived for three cases: undirected information flow (UIF) topology with identical fading channels, balanced directed information flow (BDIF) topology with identical fading channels, and general information flow topology (IFT) with nonidentical fading channels, respectively. These conditions explicitly reveal how the statistical characteristics of fading channels and IFT jointly affect vehicular stability. Second, in order to mitigate the impact of fading channels on platoon MSS, some feasible dynamic observer-based controllers by using the relative output feedback, are proposed for each one of the former two situations by solving the corresponding modified Riccati inequalities (MRIs); and in the last situation, by employing edge Laplacian to model the vehicle platoon dynamics, a sufficient condition based on the solution of an LMI, and a feasible state-based controller based on the solution of an MRI, are provided. Finally, simulations are carried out to compare three distinct fading channels, namely the Nakagami channel, Rician channel, and Rayleigh channel. The outcomes substantiate the superior and effective performance of the implemented control methods in guaranteeing the platoon MSS.

Linear quadratic tracker (LQT) is usually employed to solve unconstrained tracking problems but falls short when dealing with systems exhibiting actuator saturation. This paper presents a novel quasilinear quadratic tracking method specifically designed to address this scenario. Firstly, the stochastic linearization (SL) approach is utilized to approximate the saturation nonlinearity with equivalent gains and biases using statistical properties of its input, which are thus incorporated into the system model so as to eliminate the nonlinearity. Then, different time scales are applied in the tracking controller and states in order to improve tracking accuracy. In addition, to reduce computational complexity, two algorithms are provided for approximating the equivalent gains and biases, catering to both scalar and vector control signals. Finally, the proposed algorithms are evaluated through numerical examples, demonstrating their effectiveness and superior tracking performances.

The attack detection and data-driven resilient control problem for heterogeneous nonlinear nonaffine multi-agent systems (MASs) in the presence of intermittent false data injection (FDI) attacks is investigated in this article. First, an attack detection and isolation mechanism based on the distributed observer are designed to determine the attack signals and isolate the attacked communication links in time. Then, in order to solve the problem of the unknown system model, the dynamic linearization method is used to convert the nonlinear nonaffine MASs into an equivalent linear data model. Further, based on the linear data model, the data-driven resilient controller with the attack isolation mechanism is designed to achieve the leader-following tracking control objective. Finally, the simulation result illustrates the performance of the proposed scheme with comparisons.

This paper investigates the event-triggered finite-time trajectory tracking controller based on a type of chained-form nonholonomic systems under unknown disturbances by utilizing relay switching technology. A key design idea is that the entire control design is grouped into two separated control stages to produce different finite-time tracking controllers with correspondingly event-triggered control rules. By using some nonlinear design methods, a relay switching–based event-triggered finite-time tracking control method is adopted to assure that the resulting closed-loop tracking error system converges to an arbitrarily small neighborhood around zero within a finite time. All closed-loop error system states keep bounded throughout the entire process. Simulation and experiment results demonstrate the rationality of the designed tracking control strategy.

This article studies the guaranteed cost extended dissipative stabilization problem of switched IT2 fuzzy systems (SIT2FSs) with switching signal transmission delays and local nonlinear model. The guaranteed cost $��{�H�}_{�\infty �}�$ performance, guaranteed cost strict dissipative performance, guaranteed cost $��{�L�}_{�2�}�$ − $��{�L�}_{�\infty �}�$ performance and guaranteed cost passivity performance are considered for SIT2FSs in a unified form. First, a novel asynchronous control scheme is proposed for SIT2FSs with local nonlinear model. The controller gains in mismatched interval are designed separately. By using a premise-variable-domain-partition-dependent switched fuzzy Lyapunov functions (PDSFLFs) approach, the membership-function-shape-independent (MFSI) existence conditions of a class of IT2 fuzzy switched controllers, which can ensure the guaranteed cost extended dissipative performance of SIT2FSs, are established. Then, by utilizing the shape information of membership functions and dividing the premise variable domain into multiple partitions, the membership-function-shape-dependent (MFSD) existence conditions of a class of premise-variable-domain-partition-dependent (PVDPD) IT2 fuzzy switched controllers are presented. The results indicate that less conservative results can be achieved by using the PVDPD IT2 fuzzy switched controllers, and better system performance can be gotten compared with the Type-1 fuzzy switched controllers. Finally, the effectiveness of the results is demonstrated through a robot arm model.

The problem of event-triggered $��{�H�}_{�\infty �}�$ control for networked Takagi–Sugeno (T-S) fuzzy system under aperiodic DoS attacks and deception attacks is investigated. First, an event generator is introduced in the Sensor-to-Controller channel to determine the transmission of data. At the same time, the Sensor-to-Controller channel is assumed to be subjected to deception attacks that are randomly distributed but not Bernoulli distributed. Next, the impact of aperiodic DoS attacks on the Controller-to-Actuator channel is further considered, and the DoS attack behavior is described in terms of attack period and frequency. The article designs an adaptive resilience event-triggered mechanism (ARETM), which is aimed at circumventing the ineffective data updating in the “active” phase of the DoS attacks, thereby realizing the effective saving of communication resources and mitigating the adverse effects of DoS attacks. Then, the switched fuzzy system is established to cope with the different states of the DoS attackers. Using the piecewise Lyapunov function, a design method for the controller gains and the ARETM matrix is obtained, which allows the system to be stabilizable and obtain $��{�H�}_{�\infty �}�$ performance under the control action. Finally, the effectiveness of the ARETM-based control strategy is confirmed by simulation experiment.

This article studies a stealthy attack strategy design for distributed state estimation from the perspective of an attacker in cyber-physical systems, where both internal and external attack scenarios are considered simultaneously. To enhance robustness against outliers and reduce communication burden, a distributed fusion estimator is developed by fusing the innovation residuals of neighboring smart sensor nodes without any attack. Based on the designed distributed fusion estimator, the evolution of the distributed estimation error covariance is analyzed, and its lower and upper bounds are obtained. Moreover, a stealthy attack framework embedding adjustable parameter is designed to weaken the estimation performance, where the constraints of the adjustable parameter are provided based on the desired attack effect. Finally, a simulation example is provided to manifest the validity of the main results.

In this article, we aim to design a general framework for the pursuit-evasion (PE) game of multiple UAVs. Based on the distance between the pursuers and the evader, the whole pursuit-evasion process is decoupled into a seeking stage and a herding stage. A formation control method is proposed to make sure that the pursuers can find and drive the noncooperative evaders along a desired trajectory towards the designated target while maintaining a preset formation. In the meantime, an adaptive potential function is designed to achieve collision avoidance to both obstacles and other agents in the formation. The main contribution is that it combines formation control and collision avoidance in the problem of indirect herding, which is rarely addressed before. Also, the convergence and effectiveness of the designed controller for trajectory tracking and formation maintenance are proven and verified in the article. Simulation results in two and three dimensional space show that the proposed framework achieves the goal of coordinated herding and collision avoidance in a pursuit-evasion scenario under uncertainties and external disturbances.