Model-free adaptive command-filtered-backstepping sliding mode control for discrete-time high-order nonlinear systems

Backstepping Control for a Class of Nonlinear Discrete-Time Systems Subject to Multisource Disturbances and Actuator Saturation

In this article, the backstepping control scheme is designed for a class of systems with multisource disturbances, actuator saturation, and nonlinearities in the domain of discrete time. To address the multisource disturbances, we put forward a novel discrete-time hybrid observer, which can deal with both modeled and unmodeled disturbances. In virtue of the radial basis function neural networks, the unknown nonlinearities are approximated. In addition, the anti-windup technique is adopted to cope with the actuator saturation phenomenon, which is pervasive in engineering practice. Bearing all the adopted mechanisms in mind, the composite control strategy is designed in a backstepping manner. Sufficient conditions are established to guarantee that the states of the system ultimately converge to a small range with linear matrix inequalities. Finally, the effectiveness of the presented methodology is verified for the spacecraft attitude system.

Model-Free Cooperative Adaptive Sliding-Mode-Constrained-Control for Multiple Linear Induction Traction Systems

In order to deal with the speed cooperative control problem in the multiple linear induction traction systems consists of multiple linear induction motors, a model-free cooperative adaptive sliding-mode-constrained-control strategy is proposed considering the input magnitude and rate constraints which may cause the problem of actuator and integral saturation. First, the equivalent circuit topology of the single motor in the system is investigated. Besides, the system is considered as the multiagent system with fixed communication topology due to the interaction between adjacent motors. Then, the output observer is presented to estimate the output and the estimation algorithm of pseudo-partial derivative parameter and uncertainties is proposed. Based on the above, the proposed control scheme is presented by designing an integral sliding-mode surface containing the systematic error and an anti-windup compensator is added to eliminate the saturation. Finally, the simulations of the proposed control strategy for multiagent systems are carried out to demonstrate the effectiveness and superiority of the proposed control strategy.

Fuzzy Optimized MFAC Based on ADRC in AUV Heading Control

The control issue of Autonomous Underwater Vehicles (AUV) is very challenging since the precise mathematical model of AUV is hard to establish due to its strong coupling and time-varying features. Meanwhile, AUV movement is easily interfered with by ocean currents and waves, causing anti-interference performance of traditional Proportional-Integral-Derivative (PID) control to be unsatisfactory. Aiming to solve those problems, an algorithm of fuzzy optimized model-free adaptive control (MFAC) based on auto-disturbance rejection control (ADRC) was proposed and used in AUV heading control. The MFAC is used to overcome the difficulty with establishing a precise mathematical model, and the ADRC is introduced to handle the interference of currents and waves. In this paper, MFAC and ADRC are combined. First, the MFAC is performed based only on the I/O data of the controlled object, which is simple to implement with low calculation complexity and strong robustness. Then, a tracking differentiator (TD) is employed to track the input signal to overcome the antinomy of rapidity and hypertonicity in MFAC. After that, an extended-state observer (ESO) is added to control the variables of MFAC to estimate all the disturbances, which can greatly improve the anti-interference ability of the system. Due to the complexity and diversity of the marine environment, a fuzzy optimized MFAC based on ADRC is proposed to improve the adaptability of AUV to the marine environment. Simulations and experiments were carried out to verify the control effect of this algorithm in complex sea conditions.