A novel adaptive second-order sliding mode controller for autonomous underwater vehicles

Abstract

Navigating, directing, and controlling autonomous underwater vehicles (AUVs) are demanding and considered complicated compared to the autonomous surface-level performance. In such vehicles, the motion can be controlled depending on the estimation of indefinite hydrodynamic forces and the disturbances that occurs in this vehicle in the underwater background. In this article, Gray Wolf optimization (GWO) is performed along with the second-order sliding mode control (GW-SoSMC) approach for controlling the yaw angle in AUV. The main purpose of the article is to reduce the error that occurs in the system between the controlled signal and desired signal corresponding to yaw angle. Using this proposed model, both the occurrence of chattering and the controlling performance of AUV system can be diminished. Moreover, the proposed model is compared with the existing approaches like, FireFly-SoSMC (FF-SoSMC), Genetic Algorithm-SoSMC (GA-SoSMC), Gray Wolf-SMC (GW-SMC), Group search optimization-SoSMC (GSO-SoSMC) and Artificial Bee Colony-SoSMC (ABC-SoSMC). From the simulation results, it shows that the performance of the implemented technique in terms of steady-state response, error analysis, yaw angle analysis, and controller response is enhanced while comparing with the existing approaches.

Study of chattering suppression for the sliding mode controller of an electromagnetic levitation system

“…Sliding mode control (SMC), as an intelligent control algorithm, is well suited for the robust control of the high-order non-linear systems under complex environments due to its excellent control performance and robustness. Nowadays, SMC is successfully applied in underwater vehicle (Roy and Ghoshal, 2021), electromagnetic bearing (Wang et al, 2020b) and maglev vehicle (De Boeij et al, 2006). The basic concept of SMC is that the ideal control law makes state trajectory converge asymptotically to the sliding mode surface in the state space.…”

Enhancement of low voltage ride-through ability of the photovoltaic array aided by the MPPT algorithm connected with wind turbine

“…A new optimal model-free controller based on a sliding mode technique (Khooban, 2017; Roy and Ghoshal, 2019) is used to balance load demands and power generations in the time-delay stand-alone microgrid (MG) system (Khooban et al , 2018a) with electric vehicles (EVs). A new modified optimization algorithm, named the black hole optimization search algorithm, is applied to tune the coefficients of the novel model-free technique.…”