This paper investigates the problem of fuzzy adaptive finite-time inverse optimal control for active suspension systems (ASSs). The fuzzy logic systems (FLSs) are utilized to learn the unknown non-linear dynamics and an auxiliary system is established. Based on the finite-time stability theory and inverse optimal theory, a fuzzy adaptive inverse finite-time inverse optimal control method is proposed. It is proven that the formulated control approach guarantees the stability of the controlled systems, while ensuring that errors converge to a small neighborhood of zero within finite time. Moreover, the optimized control performance can be achieved. Eventually, the simulation results demonstrate the effectiveness of the proposed fuzzy adaptive finite-time inverse optimal control scheme.

This paper investigates the adaptive neural network (NN) event-triggered secure formation control problem for nonholonomic mobile robots (NMRs) subject to deception attacks. The NNs are employed to approximate unknown nonlinear functions in robotic dynamics. Since the transmission channel from sensor-to-controller is vulnerable to deception attacks, a NN estimation technique is introduced to estimate the unknown deception attacks. In order to alleviate the amount of communication between controller-and-actuator, an event-triggered mechanism with relative threshold strategy is established. Then, an adaptive NN event-triggered secure formation control method is proposed. It is proved that all closed-loop signals of controlled systems are bounded and the formation tracking errors converge a neighborhood of the origin in the presence of deception attacks. The comparative simulations illustrate the effectiveness of the proposed secure formation control scheme.

This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problem for a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuator faults. The UWMR system includes unknown nonlinear dynamics and immeasurable states. Fuzzy logic systems (FLSs) are utilized to work out immeasurable functions. Furthermore, with the support of the backstepping control technique and adaptive fuzzy state observer, a fuzzy adaptive finite-time output-feedback FTC scheme is developed under the intermittent actuator faults. It is testifying the scheme can ensure the controlled nonlinear UWMRs is stable and the estimation errors are convergent. Finally, the comparison results and simulation validate the effectiveness of the proposed fuzzy adaptive finite-time FTC approach.