Robust Passivity Cascade Technique-Based Control Using RBFN Approximators for the Stabilization of a Cart Inverted Pendulum
Reza Rahmani,
Saleh Mobayen,
Afef Fekih and
Jong-Suk Ro
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Reza Rahmani: Department of Electrical Engineering, Faculty of Engineering, University of Zanjan, Zanjan 45371-38791, Iran
Saleh Mobayen: Department of Electrical Engineering, Faculty of Engineering, University of Zanjan, Zanjan 45371-38791, Iran
Afef Fekih: Department of Electrical and Computer Engineering, University of Louisiana at Lafayette, Lafayette, LA 70504-3890, USA
Jong-Suk Ro: School of Electrical and Electronics Engineering, Chung-Ang University, Dongjak-gu, Seoul 06974, Korea
Mathematics, 2021, vol. 9, issue 11, 1-11
Abstract:
This paper proposes a novel passivity cascade technique (PCT)-based control for nonlinear inverted pendulum systems. Its main objective is to stabilize the pendulum’s upward states despite uncertainties and exogenous disturbances. The proposed framework combines the estimation properties of radial basis function neural networks (RBFNs) with the passivity attributes of the cascade control framework. The unknown terms of the nonlinear system are estimated using an RBFN approximator. The performance of the closed-loop system is further enhanced by using the integral of angular position as a virtual state variable. The lumped uncertainties (NN—Neural Network approximation, external disturbances and parametric uncertainty) are compensated for by adding a robustifying adaptive rule-based signal to the PCT-based control. The boundedness of the states is confirmed using the passivity theorem. The performance of the proposed approach was assessed using a nonlinear inverted pendulum system under both nominal and disturbed conditions.
Keywords: passivity cascade control; RBFN approximator; nonlinear systems; inverted pendulum (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)
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