This paper presents an adaptive control method for a class of uncertain strict-feedback switched nonlinear systems. First, we consider the constraint characteristics in the switched nonlinear systems to ensure that all states in switched systems do not violate the constraint ranges. Second, we design the controller based on the backstepping technique, while integral Barrier Lyapunov functions (iBLFs) are adopted to solve the full state constraint problems in each step in order to realize the direct constraints on state variables. Furthermore, we introduce the Lyapunov stability theory to demonstrate that the adaptive controller achieves the desired control goals. Finally, we perform a numerical simulation, which further verifies the significance and feasibility of the presented control scheme.

This paper investigates the output constraint problem for switched uncertain nonlinear systems with unknown dead-zone input. The system output is constrained by a time-varying bound, and the time-varying Barrier Lyapunov Function (BLF) is employed to guarantee that the constraint condition is not violated. The parameter of considered dead-zone is unknown but bounded. In order to remove the effectiveness caused by dead-zone, an adaptive scheme is used to adjust the bound of the unknown parameter. In addition, the unknown system dynamic is taken into account, which is modeled by using fuzzy logic systems (FLSs). Combing the backstepping technique, an adaptive controller is constructed such that all the signals in the closed-loop system are bounded under arbitrary switching signal, and the system out can track the reference signal as soon as possible. Moreover, the constraint condition for system output is ensured. Finally, an example is employed to explain the effectiveness of the proposed method.INDEX TERMS Dead-zone, fuzzy logic systems, switched systems, time-varying barrier Lyapunov function.

This paper presents an adaptive fuzzy control approach of multiple-inputmultiple-output (MIMO) switched uncertain systems, which involve time-varying full state constraints (TFSCs) and unknown disturbances. In the design procedure, the fuzzy logic systems are adopted to approximate the unknown functions in the systems. The adaptive fuzzy controller is set up by backstepping technique. According to the tangent barrier Lyapunov function (BLF-Tan), a novel adaptive MIMO switched nonlinear control algorithm is designed. Under the rule of arbitrary switchings and the proposed control laws, it is demonstrated that all signals in the resulted system are semiglobally uniformly ultimately bounded (SGUUB) and the tracking error converges to a small neighborhood of zero with TFSCs. Furthermore, the simulation example validates the effectiveness of presented control strategy. KEYWORDS full state constraints, fuzzy logic systems (FLSs), multiple-input-multiple-output (MIMO), switched systems, tangent barrier Lyapunov function (BLF-Tan) Int J Adapt Control Signal Process. 2019;33:1583-1600.wileyonlinelibrary.com/journal/acs

This paper is concerned with adaptive tracking control for switched uncertain nonlinear systems, which contain the time-varying output constraint (TVOC) and input asymmetric saturation characteristic. In response to the unknown functions, the fuzzy logic systems are adopted. The controller is constructed by the backstepping technique. Based on the Tangent Barrier Lyapunov Function (BLF-Tan), an adaptive switched control scheme is designed. It is demonstrated that all signals in the resulted system are semiglobally uniformly ultimately bounded with TVOC under arbitrary switchings. Furthermore, the effectiveness of presented control method is validated via the simulation example. KEYWORDS input asymmetric saturation, switched uncertain nonlinear systems, Tangent Barrier Lyapunov Function, time-varying output constraint 1344

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