Novel Adaptive Charged System Search algorithm for optimal tuning of fuzzy controllers

•An Adaptive Charged System Search (ACSS) algorithm is proposed.•The ACSS algorithm consists of five stages.•An ACSS-based design and tuning method for Takagi–Sugeno fuzzy controllers is offered.•The optimal tuning of fuzzy controllers with a reduced process parametric sensitivity is given. This pap...

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Veröffentlicht in:Expert systems with applications Jg. 41; H. 4; S. 1168 - 1175
Hauptverfasser: Precup, Radu-Emil, David, Radu-Codruţ, Petriu, Emil M., Preitl, Stefan, Rădac, Mircea-Bogdan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier Ltd 01.03.2014
Elsevier
Schlagworte:
Adaptive algorithms
Adaptive control systems
Algorithmics. Computability. Computer arithmetics
Algorithms
Applied sciences
Charging
Computer science; control theory; systems
Control system synthesis
Control systems
Control theory. Systems
Exact sciences and technology
Fuzzy control
Fuzzy logic-based Adaptive Charged System Search algorithms
Optimal control
Optimization
Optimization problems
Process gain sensitivity
Sensitivity models
Takagi–Sugeno PI-fuzzy controllers
Theoretical computing
Tuning
Process gain sensitivity
Fuzzy logic-based Adaptive Charged System Search algorithms
Sensitivity models
Takagi–Sugeno PI-fuzzy controllers
Optimization problems
Integral proportional control
Adaptive algorithm
Error estimation
Adaptive system
Search system
Position control
Parametric system
Non linear control
Control synthesis
Modeling
Fuzzy logic-based Adaptive Charged System
Absolute error
Fuzzy control
Takagi―Sugeno PI-fuzzy controllers
Mathematical programming
Second order equation
Output error
Sensitivity analysis
Optimal algorithm
Search algorithms
Error function
Non linear system
Search algorithm
Fuzzy logic
Measure theory
Value function
Optimal control
Objective function
Sugeno integral
ISSN:0957-4174, 1873-6793
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Zusammenfassung:•An Adaptive Charged System Search (ACSS) algorithm is proposed.•The ACSS algorithm consists of five stages.•An ACSS-based design and tuning method for Takagi–Sugeno fuzzy controllers is offered.•The optimal tuning of fuzzy controllers with a reduced process parametric sensitivity is given. This paper proposes a novel Adaptive Charged System Search (ACSS) algorithm for the optimal tuning of Takagi–Sugeno proportional–integral fuzzy controllers (T–S PI-FCs). The five stages of this algorithm, namely the engagement, exploration, explanation, elaboration and evaluation, involve the adaptation of the acceleration, velocity, and separation distance parameters to the iteration index, and the substitution of the worst charged particles’ fitness function values and positions with the best performing particle data. The ACSS algorithm solves the optimization problems aiming to minimize the objective functions expressed as the sum of absolute control error plus squared output sensitivity function, resulting in optimal fuzzy control systems with reduced parametric sensitivity. The ACSS-based tuning of T–S PI-FCs is applied to second-order servo systems with an integral component. The ACSS algorithm is validated by an experimental case study dealing with the optimal tuning of a T–S PI-FC for the position control of a nonlinear servo system.
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ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2013.07.110