Tracking control stabilization of systems manipulated by constrained parabolic nonlinear actuator

Homaeinezhad, Mohammad Reza; Ebrahimi, Mohammad Moeen

doi:10.1007/s40435-023-01365-5

Cited by 1 publication

(1 citation statement)

References 55 publications

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“…Pongfai et al proposed a parameter design methodology based on a proportionalintegral-derivative (PID)-based adaptive cluster learning process for the optimal control of MIMO systems [3]. Homaeinezhad et al proposed a Lyapunov-stability-based algorithm as a nonpredictive methodology for designing nonlinear MIMO control systems [4]. Recent studies have proposed adaptive fuzzy controllers based on sliding-mode control methods to control electric mobility, hexacopter drones, and electric wheelchairs [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Development of a Universal Adaptive Control Algorithm for an Unknown MIMO System Using Recursive Least Squares and Parameter Self-Tuning

La,

2024

Actuators

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This study proposes a universal adaptive control algorithm for an unknown multi-input multi-output (MIMO) system using recursive least squares (RLS) and parameter self-tuning. The issue of adjusting the control and system parameters in response to changes in the platform was discussed. The development of a control algorithm that can consistently achieve reliable and robust control performance in various systems is important. This study aimed to develop a control algorithm that can track the reference value for any unknown MIMO system. For the controller design, an nth-order differential error dynamic model was designed, and an RLS with a scale factor was used to estimate the coefficients of the error dynamics. In the current scenario, the numbers of control inputs and error states in the error dynamics were assumed to be equal. It was designed such that the control input is derived based on the Lyapunov stability concept using the estimated coefficients. The scale factor in the RLS and injection term in the control input based on the sliding-mode approach were computed using a self-tuning methodology. The performance of the proposed universal adaptive control algorithm was evaluated using an actual DC motor and CarMaker (version 8.1.1) software tests under various scenarios.

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Section: Introductionmentioning

confidence: 99%

Development of a Universal Adaptive Control Algorithm for an Unknown MIMO System Using Recursive Least Squares and Parameter Self-Tuning

La,

2024

Actuators

View full text Add to dashboard Cite

show abstract

Tracking control stabilization of systems manipulated by constrained parabolic nonlinear actuator

Cited by 1 publication

References 55 publications

Development of a Universal Adaptive Control Algorithm for an Unknown MIMO System Using Recursive Least Squares and Parameter Self-Tuning

Development of a Universal Adaptive Control Algorithm for an Unknown MIMO System Using Recursive Least Squares and Parameter Self-Tuning

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