2019
DOI: 10.3390/info10020038
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Development of a New Adaptive Backstepping Control Design for a Non-Strict and Under-Actuated System Based on a PSO Tuner

Abstract: In this work, a new adaptive block-backstepping control design algorithm was developed for an under-actuated model (represented by a ball–arc system) to enhance the transient and steady-state behaviors and to improve the robustness characteristics of the controlled system against parameter variation (load change and model uncertainty). For this system, the main mission of the proposed controller is to simultaneously hold the ball at the top of the arc and retain the cart at the required position. The stability… Show more

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Cited by 32 publications
(20 citation statements)
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“…In this paper, the control goal is to determine the control law that makes the angular position of the pendulum's ball tracks the desired angular position [3,14]. The output position error (…”
Section: Backstepping Controller Designmentioning
confidence: 99%
See 1 more Smart Citation
“…In this paper, the control goal is to determine the control law that makes the angular position of the pendulum's ball tracks the desired angular position [3,14]. The output position error (…”
Section: Backstepping Controller Designmentioning
confidence: 99%
“…Consequently, various types of backstepping control algorithms have been used for controlling various nonlinear systems such as adaptive backstepping controller [3], the integral backstepping controller [4], the optimal backstepping controller [5], the fuzzy backstepping controller [6], backstepping sliding mode controller [7], backstepping based PID controller [8], backstepping /nonlinear H∞ controller [9], and adaptive type-2 fuzzy backstepping controller [10].…”
Section: Introductionmentioning
confidence: 99%
“…In this paper, a PSO algorithm was adopted for autonomous tuning and to find optimal values of these parameters. 19,20 The problem of PSO can be defined as 27…”
Section: Optimization Of the Design Parameters For The Super-twistingmentioning
confidence: 99%
“…This old technique could not find the optimal dynamic performance of the controlled system based on the proposed controllers. Therefore, a modern optimization technique is used to tune these design parameters to improve the dynamic performance of the controlled system [ 28 , 29 ]. In the present work, the Particle Swarm Optimization (PSO) has been suggested to adjust the design parameters of the controlled system.…”
Section: Introductionmentioning
confidence: 99%