Adaptive Fault-Tolerant Boundary Control for a Flexible String With Unknown Dead Zone and Actuator Fault

Disturbance Observer-Based Adaptive Intelligent Control of Marine Vessel With Position and Heading Constraint Condition Related to Desired Output

This article studies the adaptive control about the geodetic fixed positions and heading of three-degree-of-freedom dual-propeller vessel. During the navigation of a vessel at sea, due to the unpredictable sea, on the one hand, it is important to ensure that the vessel can smoothly follow the desired geodesic fixed position and heading; on the other hand, when the sailing environment is harsh, it is even more important that the vessel can adapt to the desired geodesic fixed position and heading that change at any time for safe driving. Therefore, this article selects the time-varying function related to the desired geodesic fixed position and heading as the constraint condition, and the constraint condition will change in real time as the expected position and heading change. The design of the control strategy is difficult, and the designed control strategy will be more suitable for complex maritime navigation conditions. First, the article constructs a log-type barrier Lyapunov function. Second, by introducing an unknown external disturbance observer, the external disturbances caused by the environment that may be encountered during the vessel's voyage can be observed. Then, combined with the backstepping algorithm, a neural network (NN) control strategy and adaptive law are designed. Among them, for the uncertain function in the process of designing the control strategy, the NN is used to approximate it. Furthermore, through the Lyapunov stability analysis, it is shown that applying the designed control strategy to the vessel system in this article can ensure that the system is closed-loop stable. The final simulation experiment shows the effectiveness of the designed control strategy.

Finite-Time Neural Network Fault-Tolerant Control for Robotic Manipulators under Multiple Constraints

In this study, a backstepping-based fault-tolerant controller for a robotic manipulator system with input and output constraints was developed. First, a barrier Lyapunov function was adopted to ensure that the system output satisfied time-varying constraints. Subsequently, the actuator input saturation and asymmetric dead-zone characteristics were also considered, and the actuator characteristics were described using a continuous function. The impacts of actuator failures and unknown dynamical parameters of the system were eliminated by employing Gaussian radial basis function neural networks. The external disturbances were compensated for, using a disturbance observer. Meanwhile, a finite-time dynamic surface technique was adopted to accelerate the convergence of the system errors. Finally, simulation of a 2-degrees-of-freedom robotic manipulator system showed the effectiveness of the proposed controller.

Finite-time stabilization and H∞ control of Port-controlled Hamiltonian systems with disturbances and saturation

The finite-time stabilization and finite-time H_∞ control problems of Port-controlled Hamiltonian (PCH) systems with disturbances and input saturation (IS) are studied in this paper. First, by designing an appropriate output feedback, a strictly dissipative PCH system is obtained and finite-time stabilization result for nominal system is given. Second, with the help of the Hamilton function method and truncation inequality technique, a novel output feedback controller is developed to make the PCH system finite-time stable when IS occurs. Further, a finite-time H_∞ controller is designed to attenuate disturbances for PCH systems with IS, and sufficient conditions are presented. Finally, a numerical example and a circuit example are given to reveal the feasibility of the obtained theoretical results.