Composite nonlinear feedback–based adaptive integral sliding mode control for a servo position control system subject to external disturbance

This paper presents a composite nonlinear feedback–based adaptive integral sliding mode controller with a reaching law (CNF-AISMRL) for fast and accurate control of a servo position control system subject to external disturbance. The proposed controller exploits the advantages of composite nonlinear feedback (CNF) and sliding mode control (SMC) schemes to improve the transient performance and increase the robustness of the closed-loop system. An integral sliding mode combined with a quick reaching law is designed to eliminate the effect of disturbances, which mitigates chattering and achieves finite-time convergence of the sliding mode. An adaptation tuning approach is utilized to deal with unknown but bounded system uncertainties and disturbances. When considering the model uncertainties and disturbances, the stability of the closed-loop system is verified based on the Lyapunov theorem. Numerical simulations are investigated to the effectiveness of the proposed scheme. The transient performance of load disk position to step signal with disturbances using CNF, composite nonlinear feedback based integral sliding mode control (CNF-ISM), and the proposed CNF-AISMRL schemes is given. The simulation results indicate that, without acquiring the knowledge of bounds on system disturbances, the proposed control scheme has superior performance in the presence of time-varying disturbances.

Low-conservative robust composite nonlinear feedback control for singular time-delay systems

A low-conservative composite nonlinear feedback controller is proposed for singular time-delay systems with time-varying delay. The proposed composite nonlinear feedback controller not only improves the transient responses of the closed-loop system but it also has less conservatism than other composite nonlinear feedback controllers. The gain of the linear part of the composite nonlinear feedback controller is obtained by precise mathematical calculation to depend not only on the upper bound of the delay but also on the delay range and rate of its changes. More advantages of the proposed composite nonlinear feedback controller are its accurate operation in the presence of actuator saturation, model uncertainties, and system singularities. The linear and nonlinear parts of the proposed controller are designed by solving a linear matrix inequality problem confirmed through a theorem using Lyapunov stability analysis. The theoretical achievements are endorsed by computer simulation through numerical and practical examples.

Enhanced Composite Nonlinear Control Technique using Adaptive Control for Nonlinear Delayed Systems

Background and Introduction: The proposed control law is designed to provide fast reference tracking with minimal overshoot and to minimize the effect of unknown nonlinearities and external disturbances. Methods: In this work, an enhanced composite nonlinear feedback technique using adaptive control is developed for a nonlinear delayed system subjected to input saturation and exogenous disturbances. It ensures that the plant response is not affected by adverse effect of actuator saturation, unknown time delay and unknown nonlinearities/ disturbances. The analysis of stability is done by Lyapunov-Krasovskii functional that guarantees asymptotical stability. Results: The proposed control law is validated by its implementation on exothermic chemical reactor. MATLAB figures are provided to compare the results. Conclusion: The simulation results of the proposed controller are compared with the conventional composite nonlinear feedback control which illustrates the efficiency of the proposed controller.

Impaired Driver Assistance Control With Gain-Scheduling Composite Nonlinear Feedback for Vehicle Trajectory Tracking

Impaired drivers have deteriorated driving performances that may greatly endanger the road safety. It is challenging to design assistance controllers for the impaired drivers because the impaired driver behaviors are difficult to be modeled and considered in the controller design. To this end, this paper proposes a gain-scheduling composite nonlinear feedback (GCNF) controller to assist the impaired drivers. A driver-vehicle system containing the impaired driver model is developed. The steering behaviors of the impaired drivers are described by deteriorating the driver model parameters and including the driver uncertainties. Based on the driver-vehicle system, a GCNF controller integrating the gain-scheduling technique, the weighted H∞ performance, and the composite nonlinear feedback algorithm is designed to handle the declined driving performances and improve the transient performances. The designed GCNF controller is validated in the carsim simulations. The simulation results show that the GCNF controller can effectively assist the impaired drivers of different impaired levels to reduce the trajectory tracking errors and improve the driving performances.

Robust composite nonlinear feedback control for uncertain robot manipulators

On the basis of the classical computed torque control method, a new composite nonlinear feedback design method for robot manipulators with uncertainty is presented. The resulting controller consists of the composite nonlinear feedback control and robust control. The core is to use the robust control for online approximation of the system’s uncertainty as a compensation term for the composite nonlinear feedback controller. The design method of the new controller is given, and the convergence of the closed-loop system is proved. The simulation results show that the proposed scheme can make the uncertain robot system have strong robustness and anti-interference ability.