Design and Implementation of Adaptive Backstepping Control for Position Control of Propeller-Driven Pendulum System

Abstract

The performance of the classical and adaptive backstepping control schemes for the angular position control of a nonlinear Propeller-Driven Pendulum System (PDPS) is investigated in this paper. A Particle Swarm Optimization (PSO) algorithm has been utilized to tune the design parameters of the proposed controllers. Based on the Lyapunov stability analysis the classical and the Adaptive Back-Stepping Controllers have been constructed in order to prove the convergence of the system's error with time. The Adaptive Backstepping Controller (ABSC) is designed to compensate for the variation in the system's mass magnitude. In terms of system transient response, a comparison study of the effectiveness of both controllers has been presented in this work. The simulation results have been obtained based on the MATLAB software. In addition, a comparison study between the proposed controllers and other controllers has been listed to demonstrate the effectiveness of the proposed controller. The simulation results show that the PSO based classical Backstepping Controller (BSC) has a better performance in terms of reducing the settling time, the steady-state error, and the Root Mean Square Error (𝑅𝑀𝑆𝐸) value in comparison with the STSMC and SMC. In addition, the simulation results reveal that the PSO based ABSC has a better performance in terms of reducing the steady state error and the maximum overshoot in comparison with the PSO based BSC and ASTSMC.

Hunting Search Algorithm-Based Adaptive Fuzzy Tracking Controller for an Aero-Pendulum

“…The methodology proposed in this paper shows better results than those presented in Refs. [19,20], where a PSO algorithm is utilized. The analysis of an aero-pendulum is presented in [20].…”

“…[19,20], where a PSO algorithm is utilized. The analysis of an aero-pendulum is presented in [20]. The methodology is well-described, with two parameters to optimize being proposed for a backstepping controller.…”

“…Additionally, utilizing the particle swarm optimization (PSO) algorithm to determine optimal PID controller gains underscores the innovative nature of the proposed strategy, offering a systematic and efficient means to enhance the system performance. Furthermore, the authors in [20] reported the performance of classical and adaptive backstepping control schemes for the angular position control of an aero-pendulum where a PSO algorithm is utilized to tune the design parameters of the controllers. The Classical and Adaptive Back-Stepping Controllers have been developed based on Lyapunov stability analysis to establish the convergence of the system's error over time.…”

Design of an Adaptive Integral Sliding Mode Controller for Position Control of Electronic Throttle Valve

“…For controlling such controlled plants with high nonlinear features and parameter uncertainty, backstepping controller and sliding mode control are dependable control techniques. The Backstepping controller performs well and has good qualities for controlling the ETV's position [11][12][13][14][15][16]. Because the sliding-mode control may asymptotically stabilize the system, it has been widely used in real-world applications [17][18][19][20][21][22].…”

Optimal Control Design for Propeller Pendulum Systems Using Gorilla Troops Optimization

“…The simple pendulum system is a standard topic in most physics educational courses because it includes some physical subjects including the simple harmonic motion, the acceleration of gravity, and the center of mass [2]. Besides, the system is considered a nonlinear model that can be used in the education of mechatronics, control, and mechanical engineering to explain the system dynamics and methods of controller design [3]. Moreover, the propeller pendulum system can be used to model the take-off and landing of aircraft [4].…”