Gliding-Guided Projectile Attitude Tracking Controller Design Based on Improved Adaptive Twisting Sliding Mode Algorithm

The finite-time attitude tracking control for gliding-guided projectile with unmatched and matched disturbance is investigated. An adaptive variable observer is used to provide estimation for the unmeasured state which contains unmatched disturbance. Then, an improved adaptive twisting sliding mode algorithm is proposed to compensate for the matched disturbance dynamically with better transient quality. Finally, a proof of the finite-time convergence of the closed-loop system under the disturbance observer and the adaptive twisting sliding mode-based controller is derived using the Lyapunov technique. This attitude tracking control scheme does not require any information on the bounds of uncertainties. Simulation results demonstrate that the proposed method which is able to acquire the minimum possible values of the control gains guaranteeing the finite-time convergence performs well in chattering attenuation and tracking precision.

Enhanced sliding mode controller performance in DC-DC buck converter using a tan hyperbolic reaching law and constant plus proportional reaching law

This paper presents an enhanced sliding mode controller (SMC) operation, chattering analysis and loading conditions of the SMC DC-DC buck converter. Sliding mode portion, chattering attenuation are analyzed by using a conventional and proposed reaching law in buck converter. A proposed tan hyperbolic reaching law (THRL) is originated to be useful in terms of chattering mitigation and fast convergence. The major drawback of the conventional reaching law viz, it bypasses the main portion of the sliding mode portion to ensure fast reaching. It causes more chattering, more time to reach the steady state on the switching surface. The most significant improvement of SMC is that it guarantees strengthening the sliding mode phase. The proposed tan hyperbolic reaching law is being hit here during an exponential adjustment so that the attributes of it, covers complete sliding mode portion, chattering mitigation and fast reaching time. In turn, cause fewer switching loss in the buck converter. Even external disturbances and uncertainty of the system occurs. The loading conditions are applied to proposed tan hyperbolic reaching law and analyzed. Simulation analysis conducted by MATLAB/Simulink.

Model Predictive Super-Twisting Sliding Mode Control for an Autonomous Surface Vehicle

This paper presents a new robust Model Predictive Control (MPC) algorithm for trajectory tracking of an Autonomous Surface Vehicle (ASV) in presence of the time-varying external disturbances including winds, waves and ocean currents as well as dynamical uncertainties. For fulfilling the robustness property, a sliding mode control-based procedure for designing of MPC and a super-twisting term are adopted. The MPC algorithm has been known as an effective approach for the implementation simplicity and its fast dynamic response. The proposed hybrid controller has been implemented in MATLAB / Simulink environment. The results for the combined Model Predictive Super-Twisting Sliding Mode Control (MP-STSMC) algorithm have shown that it significantly outperforms conventional MPC algorithm in terms of the transient response, robustness and steady state response and presents an effective chattering attenuation in comparison with the Super-Twisting Sliding Mode Control (STSMC) algorithm.

High-Performance Control Technology of Buck Inverter Used for Super-Precision Machining of Composite Materials

An effective technique, genetic-feedforward sliding mode-fractional PI controlled buck inverter used for super-precision machining of composite materials is proposed. The obstruction using sliding mode control (SMC) is due to the strong chattering that severely limits its practical applicability. The chattering yields high voltage distortion in buck inverter output, thus degrading stability and reliability of super-precision machining of composite materials. The modification structure to fractional PI has been established through the plant extending way so that the chattering is diminished and better flexibility in adjusting system response can be provided. The feedforward compensator improves the dynamics response further. The genetic algorithm (GA) can be adopted for determining optimal fractional proportional-integral (FPI) parametric values. With this control technique, the TI microprocessor-based buck inverter is implemented, and then experiments illustrate that the presented technique produces less steady-state inaccuracy, chattering attenuation, loading interference rejection and parametric variation removal.