Variable Structure Adaptive Backstepping Controller for plants with arbitrary relative degree based on modular design

Queiroz, Kurios; Araujo, Aldayr D.; Fernandes, Marcus V. A.; Dias, Samaherni; Oliveira, Jackson Araújo de

doi:10.1109/acc.2010.5530717

Cited by 3 publications

(3 citation statements)

References 15 publications

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“…Variable Structure Model Reference Adaptive Control (VS-MRAC) has been widely investigated and developed in both theoretical aspects and real world applications over the past few decades (Fernandes et al, 2010; Gaeta and Montanaro, 2014; Han et al, 2007; Lee and Singh, 2012; Oliveira et al, 2007; Queiroz et al, 2010; Saedodin et al, 2010; Teixeira et al, 2013; Trajkov et al, 2008; Xu and Yan, 2008; Demetriou, 2002; Yan, 2000). It consists of combining two known approaches, namely, variable structure control (Hsu and Costa, 1989; Sabanovic et al, 2004; Nunes, 2006), known for its robustness against unmodelled dynamics, and the model reference adaptive control (Ioannou and Sun, 1996; Tao, 2003), known for its tracking capability.…”

Section: Introductionmentioning

confidence: 99%

“…This blending has received a lot of attention from many researchers (Hsu and Costa, 1989; Lee and Singh, 2012; Oliveira et al, 2007; Queiroz et al, 2010; Xu and Yan, 2008; Mohammadi, 2006) due to its many advantages. Some appealing features of the VS-MRAC schemes are the global stability, the good transient behaviour, the insensitivity to parameter variations, the rejection of external disturbances and the robustness to unmodelled dynamics.…”

Section: Introductionmentioning

confidence: 99%

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Discrete variable structure model reference adaptive control using only input-output measurements

Znidi

Dehri

Nouri

2016

Transactions of the Institute of Measurement and Control

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Designing an adequate controller for a plant with an arbitrary relative degree is still an active area of research. In this paper, a discrete variable structure model reference adaptive control using only input-output measurements (DVS-MRAC-IO) for not strictly positive real systems with a relative degree of two is proposed. In order to show the effectiveness of the proposed controller, a detailed stability analysis is studied using Lyapunov theory. Further, a straightforward generalization of DVS-MRAC-IO for systems with arbitrary relative degree is presented. Numerical results are used to show the effectiveness of the proposed methods.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Discrete variable structure model reference adaptive control using only input-output measurements

Znidi

Dehri

Nouri

2016

Transactions of the Institute of Measurement and Control

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“…The backstepping design strategy also used to develop a Lyapunov-based nonlinear controller for a hydraulic servo system which incorporates load, hydraulic, and valve dynamics in the design process [10]. In addition, combination of backstepping with variable structure and adaptive controller for plants with relative degree one is presented using input/output measurements [11]. Switching laws are used to increase robustness to parametric uncertainties and disturbances and improve transient response of the system.…”

Section: Introductionmentioning

confidence: 99%

Performance Comparison of Particle Swarm Optimization and Gravitational Search Algorithm to the Designed of Controller for Nonlinear System

Rozali

Rahmat

Husain

2014

Journal of Applied Mathematics

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This paper presents backstepping controller design for tracking purpose of nonlinear system. Since the performance of the designed controller depends on the value of control parameters, gravitational search algorithm (GSA) and particle swarm optimization (PSO) techniques are used to optimise these parameters in order to achieve a predefined system performance. The performance is evaluated based on the tracking error between reference input given to the system and the system output. Then, the efficacy of the backstepping controller is verified in simulation environment under various system setup including both the system subjected to external disturbance and without disturbance. The simulation results show that backstepping with particle swarm optimization technique performs better than the similar controller with gravitational search algorithm technique in terms of output response and tracking error.

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Modular variable structure adaptive backstepping controller: Design and stability analysis

Queiroz

Dias

Araujo

2014

Journal of the Franklin Institute

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Variable Structure Adaptive Backstepping Controller for plants with arbitrary relative degree based on modular design

Cited by 3 publications

References 15 publications

Discrete variable structure model reference adaptive control using only input-output measurements

Discrete variable structure model reference adaptive control using only input-output measurements

Performance Comparison of Particle Swarm Optimization and Gravitational Search Algorithm to the Designed of Controller for Nonlinear System

Modular variable structure adaptive backstepping controller: Design and stability analysis

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