Fuzzy fractional-order adaptive robust feedback linearization control optimized by the multi-objective artificial hummingbird algorithm for a nonlinear ball–wheel system

For stabilizing a nonlinear ball–wheel system, this research suggests a fuzzy fractional-order adaptive robust feedback linearization control approach. The feedback linearization-based controller uses the decoupled sliding mode to locate the sliding surfaces and determine the adaptive coefficients....

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Bibliographic Details
Published in:Journal of the Brazilian Society of Mechanical Sciences and Engineering Vol. 45; no. 11; p. 575
Main Authors: Arbatsofla, S. Moghtader, Mazinan, A. H., Mahmoodabadi, M. J., Nekoui, M. A.
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2023
Springer Nature B.V
Subjects:
Algorithms
Archives & records
Calculus
Control systems
Control theory
Controllers
Design engineering
Dynamical systems
Engineering
Feedback linearization
Fuzzy logic
Genetic algorithms
Kinematics
Mechanical Engineering
Optimization
Parameter estimation
Pareto optimum
Performance evaluation
Robust control
Sliding mode control
Systems stability
Technical Paper
Robust control
Fuzzy system
Multi-objective artificial hummingbird algorithm
Optimal control
Feedback linearization
Adaptive control
Fractional calculus
ISSN:1678-5878, 1806-3691
Online Access:Get full text
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Summary:For stabilizing a nonlinear ball–wheel system, this research suggests a fuzzy fractional-order adaptive robust feedback linearization control approach. The feedback linearization-based controller uses the decoupled sliding mode to locate the sliding surfaces and determine the adaptive coefficients. Then, the fractional-order calculus and fuzzy logic-based systems are implemented to improve the efficiency of the controller. Additionally, the multi-objective artificial hummingbird algorithm (MAHA) is employed to optimize the control coefficients by including two objective functions, namely the integral of the absolute values of the control efforts and the system errors. The success of the suggested strategy is then evaluated by applying it on the ball–wheel system and comparing the outcomes to those documented in the literature.
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ISSN:1678-5878
1806-3691
DOI:10.1007/s40430-023-04455-9