This paper proposes a new adaptive controller for a class of uncertain nonlinear systems with a quantized signal. Fuzzy logic systems are utilized to approximate nonlinear terms without imposing prior matching conditions required. A hysteretic type of quantizer is incorporated to reduce chattering. A new adaptive backstepping controller is designed to guarantee that the underlying uncertain nonlinear system is semiglobally uniformly ultimately bounded. Two numerical examples are presented to demonstrate the effectiveness and potential of the proposed techniques.

This paper aims at the fault-tolerant adaptive control for the nonlinearly parameterized systems with mismatched disturbances. A novel adaptive control scheme is developed in this paper by adding a power integrator technique. The mismatched disturbances are estimated by a designed disturbance observer. A new fault-tolerant control method is proposed to deal with the uncertain actuator faults including actuator stuck. The proposed adaptive controller ensures that the closed-loop system is input-to-state stable. Simulation results for a robotic arm system are given to present the effectiveness of the developed control technique.

In this paper, we study the consensus tracking problem for high-order nonlinear uncertain multiagent systems. By using the fixed-time control technique and the modified addition of a power integrator method, a novel distributed observer-based consensus protocol is proposed. Compared with the existing results in the literature, the proposed protocol can achieve consensus tracking in a fixed time independent of initial conditions even in the presence of unknown parameters and nonlinear uncertainties bounded by positive functions. Simulation examples are given to illustrate the effectiveness of the theoretical results.

The current study proposes a novel output feedback event-triggered control scheme for nonlinear systems considering state quantization. Firstly, we construct a state observer to track the unavailable system states. Secondly, a dynamic event-triggered and quantized mechanism is constructed to handle the state sampling and quantization. Then, based on the input-to-state stability (ISS) method, the asymptotic stability is ensured for the closed-loop systems. Moreover, we propose an event-triggered and quantized control scheme for the nonlinear systems with input delay, and the asymptotic stability is ensured using the Lyapunov-Krasovskii functional method. The proposed output feedback event-triggered and quantized mechanisms can guarantee a positive lower bound of the transmission interval times of communication channels, which means that the Zeno behavior is avoided. Finally, a simulation example is presented to verify the feasibility of the proposed control schemes.

This work investigates the adaptive fixed-time disturbance rejection control issue for a class of time-delay nonlinear systems subject to event-triggered and quantized input signals. First, a disturbance observer is proposed to promote the controller design. Compared with the related disturbance observer design, the observer designed in this paper can be used to construct the fixed-time control scheme. Then, combined with the backstepping technique and fuzzy logic systems (FLSs), an adaptive fuzzy event-triggered and quantized fixed-time control scheme is designed. Moreover, to deal with the unknown time delays, the Lyapunov-Krasovskii functional method is utilized to achieve the system stability. The proposed control algorithm reduces the transmission burden of data channel with a new combined event-based sampling and quantization, and improves the robustness of the time-delay nonlinear system. Finally, a numerical example and a practical example are given to validate the feasibility of the control scheme.

In this paper, the adaptive tracking problem is investigated for switched uncertain nonlinear systems with input saturation and unmodeled dynamics. An auxiliary system is introduced to analyze the effect of input saturation. Unmodeled dynamics are dominated by constructing appropriate Lyapunov functions. Under suitable conditions, a new adaptive tracking controller and a proper switching law are designed by combining the multiple Lyapunov functions (MLFs) method and the backstepping technique. It is shown that the boundedness of the closed-loop system is guaranteed, and the tracking error between the output and the reference signal can be ultimately bounded. An example is provided to demonstrate the validity of the proposed control scheme.