This paper proposes a novel fault tolerant control strategy for dynamic positioning of unmanned marine vehicles using the quantized feedback sliding mode control technique. Due to the complex ocean environment, the unmanned marine vehicles are modeled as the Takagi-Sugeno fuzzy system with unknown membership functions. When the membership functions are not available, traditional sliding mode control technique becomes infeasible. To tackle this difficulty, a novel quantized sliding mode control strategy based on switching mechanism is designed to compensate for thruster faults effects. In addition, the phenomenon of time-varying delay leads to conservativeness of the existing dynamic quantization parameter adjustment strategy. Then a larger quantization parameter adjustment range, by taking time delay and fault factor into account, is given. Combining the novel sliding mode controller design and the improved dynamic quantization parameter adjustment strategy, the dynamic positioning of unmanned marine vehicles with thruster faults and quantization can be maintained. Finally, the effectiveness of the proposed method is verified through the simulation comparison results.

This article investigates a fault-tolerant control problem for heterogeneous vehicular platoons with actuator faults and saturation. The occurrence of actuator faults may yield large control signals to avoid performance loss, which can potentially lead to saturation of the actuator that may cause further performance deterioration or even instability. To compensate for the effects of actuator faults and saturation, an adaptive fault-tolerant control method is proposed based on nonlinear vehicle dynamics and a new quadratic spacing policy. The improved quadratic spacing policy is introduced to remove the assumption of zero initial spacing errors. The nonlinear vehicle dynamics is approximated by a radial basis function neural network (RBFNN). The adaptive fault-tolerant platoon control method is developed in the context of PID-type sliding mode control technique, and proved to be capable of guaranteeing individual vehicle stability, string stability and traffic flow stability. The effectiveness of the method is verified through comparison simulation studies.

This paper investigates the fault-tolerant control problem for heterogeneous vehicular platoons where input quan- tization and dead-zone nonlinearity are also involved. Due to the occurrence of actuator faults, the maximum acceleration changes, which may invalid the traditional quadratic spacing policy. To tackle the dilemma, an improved quadratic spacing policy with the lower bound of fault factor is proposed. Furthermore, the improved quadratic spacing policy removes the assumption of zero initial spacing errors. Based on the new spacing policy, an adaptive fault-tolerant platoon control scheme is developed, by employing radial basis function neural networks (RBFNN) and PID-type sliding mode control method. The given scheme is proved to be capable of guaranteeing individual vehicle stability, string stability and traffic flow stability. The effectiveness of the scheme is verified through comparison simulation studies.

This article aims to develop a robust model predictive control (MPC) scheme for the trajectory tracking control of autonomous underwater vehicles (AUVs) subject to bounded disturbances. Based on the error dynamics model derived from the AUV dynamics and the desired trajectory, an improved tube-based MPC scheme is then developed. The tube-based MPC solves two optimal control problems, the first solves a standard problem for the nominal system which defines a reference state trajectory, and the other attempts to steer the state of the disturbed system to stay in a tube centered around the reference state trajectory thereby enabling robust control of the AUV systems. For tube-based nonlinear MPC, finding a local linear feedback to characterize the tube is challenging. To address it, we replace the local linear feedback controller with an ancillary one that incorporates the tightening constraints to ensure the disturbed system state stays in the online optimized tube. The simulation results demonstrate the effectiveness of the proposed method.

This article is concerned with the quantized output-feedback control problem for unmanned marine vehicles (UMVs) with thruster faults and ocean environment disturbances via a sliding-mode technique. First, based on output information and compensator states, an augmented sliding surface is constructed and sliding-mode stability through linear matrix inequalities can be guaranteed. An improved quantization parameter dynamic adjustment scheme, with a larger quantization parameter adjustment range, is then given to compensate for quantization errors effectively. Combining the quantization parameter adjustment strategy and adaptive mechanism, a novel robust sliding-mode controller is designed to guarantee the asymptotic stability of a closed-loop UMV system. As a result, a smaller lower bound of the thruster fault factor than that of the existing result can be tolerated, which brings more practical applications. Finally, the comparison simulation results have illustrated the effectiveness of the proposed method.

This paper investigates quantized sliding mode control of unmanned marine vehicles (UMVs) with thruster faults and nonlinearities. We give a unified model to accommodate different types of thruster faults (e.g., partial, total, time-varying stuck, hard-over, and bias faults) in a common framework, which is significant because existing methods can only address them separately in a fault-specific manner. To eliminate the quantization effect induced by the communication channel by which the UMV outputs (e.g., position and velocity) and the control inputs are transmitted to and from the remote control station, a new dynamic uniform quantizer with an adjustable range of sensitivity is given. Via flexible choice of parameters, the adjustment range can fall within that of the existing results in the fault-free case. A quantized sliding mode controller and a dynamic quantization parameter adjustment strategy are then developed to suppress oscillation amplitudes of the yaw velocity error and the yaw angle in the presence of thruster faults. Simulation studies have verified the effectiveness of the proposed method.