In this technical note, the sliding-mode control (SMC) problem is investigated for T-S fuzzy-model-based nonlinear Markovian jump singular systems subject to matched/unmatched uncertainties. To accommodate the model characteristics of such a hybrid system, a novel integral-type fuzzy sliding surface is put forward by taking the singular matrix and state-dependent projection matrix into account simultaneously, which is the key contribution of the note. The designed surface contains two important features: 1) local input matrices for different subsystems in the same system mode are allowed to be different; and 2) the matched uncertainties are completely compensated, and the unmatched ones are not amplified during sliding motion. Sufficient conditions for the stochastic admissibility of the corresponding sliding-mode dynamics are presented, and a fuzzy SMC law is constructed to ensure the reaching condition despite uncertainties. The applicability and effectiveness of our approach are verified by simulations on an inverted pendulum system.

Notice of Violation of IEEE Publication Principles After careful consideration by a duly constituted committee, an author of this article, Hamid Reza Karimi, was found to have acted in violation of the IEEE Principles of Ethical Publishing by artificially inflating the number of citations to this article. This paper is concerned with dissipativity-based fuzzy integral sliding mode control (FISMC) of continuous-time Takagi-Sugeno (T-S) fuzzy systems with matched/unmatched uncertainties and external disturbance. To better accommodate the characteristics of T-S fuzzy models, an appropriate integral-type fuzzy switching surface is put forward by taking the state-dependent input matrix into account, which is the key contribution of the paper. Based on the utilization of Lyapunov function and property of the transition matrix for unmatched uncertainties, sufficient conditions are presented to guarantee the asymptotic stability of corresponding sliding mode dynamics with a strictly dissipative performance. A FISMC law is synthesized to drive system trajectories onto the fuzzy switching surface despite matched/unmatched uncertainties and external disturbance. A modified adaptive FISMC law is further designed for adapting the unknown upper bound of matched uncertainty. Two practical examples are provided to illustrate the effectiveness and advantages of developed FISMC scheme.

In this paper, the formation control of unmanned surface vehicles (USVs) is addressed considering actuator saturation and unknown nonlinear items. The algorithm can be divided into two parts; one is steering the leader USV to trace along the desired path and the other is steering the follower USV to follow the leader in the desired formation. In the proposed formation control framework, a virtual USV is first constructed so that the leader USV can be guided to the desired path. To solve the input constraint problem, an auxiliary is introduced, and the adaptive fuzzy method is used to estimate the unknown nonlinear items in the USV. To keep the desired formation, the desired velocities of follower USVs are deduced by using geometry and Lyapunov stability theories. The stability of the closed-loop system is also proved. Finally, the effectiveness of the proposed approach is demonstrated by the simulation and experimental results.

This article investigates the problem of path following for the underactuated unmanned surface vehicles (USVs) subject to state constraints. A useful control algorithm is proposed by combining the backstepping technique, adaptive dynamic programming (ADP), and the event-triggered mechanism. The presented approach consists of three modules: guidance law, dynamic controller, and event triggering. First, to deal with the ``singularity'' problem, the guidance-based path-following (GBPF) principle is introduced in the guidance law loop. In contrast to the traditional barrier Lyapunov function (BLF) method, this article converts the USV's constraint model to a class of nonlinear systems without state constraints by introducing a nonlinear mapping. The control signal generated by the dynamic controller module consists of a backstepping-based feedforward control signal and an ADP-based approximate optimal feedback control signal. Therefore, the presented scheme can guarantee the approximate optimal performance. To approximate the cost function and its partial derivative, a critic neural network (NN) is constructed. By considering the event-triggered condition, the dynamic controller is further improved. Compared with traditional time-triggered control methods, the proposed approach can greatly reduce communication and computational burdens. This article proves that the closed-loop system is stable, and the simulation results and experimental validation are given to illustrate the effectiveness of the proposed approach.

This article presents a fault-tolerant tracking control strategy for Takagi–Sugeno fuzzy model-based nonlinear systems which combines integral sliding mode control with adaptive control technique. Two common actuator faults: 1) loss of effectiveness and 2) increased bias input, are considered simultaneously. The fuzzy tracking control system is first established by incorporating the integral term of the output tracking error. Then, an appropriate fuzzy integral switching surface is designed such that the corresponding sliding motion only suffers from the unamplified unmatched disturbance. The solution of the nominal tracking controller can be transformed into a to convex optimization problem. In particular, an adaptive fuzzy sliding mode tracking controller is synthesized to ensure the accessibility of the sliding motion despite the effect of actuator faults and unknown disturbances. Finally, the proposed tracking strategy is verified by applying it to the dynamic positioning control of unmanned marine vehicles.

This article focuses on static output feedback control for fuzzy Markovian switching singularly perturbed systems (FMSSPSs) with deception attacks and asynchronous quantized measurement output. Different from the previous work, both the logarithmic quantizer and the static output feedback controller are dependent on the operation system; by means of hidden Markov models, their modes run asynchronously with that of FMSSPSs. Additionally, the deception attacks are guided by a Bernoulli variable, and nonlinear characteristics are modeled by the Takagi–Sugeno fuzzy model. By resorting to a mode-dependent Lyapunov functional, several criteria are acquired and strictly $(\mathscr {Q},\mathscr {S},\mathscr {R})\text{--}\gamma$ -dissipative of FMSSPSs can be ensured. Finally, a dc motor model is expressed to illustrate the effectiveness of the asynchronous control scheme.