Whale Optimization Algorithm-Based Tuning of Low-Cost Fuzzy Controllers with Reduced Parametric Sensitivity

This paper proposes a novel application of Whale Optimization Algorithm (WOA) as solution for solving a complex control design and tuning problem concerning fuzzy control systems that control processes modeled as second-order servo systems with an integral component and variable parameters. The minimization of objective functions containing the error of the controlled process and the output sensitivity functions of the sensitivity models defined with respect to the parametric variations of the controlled process (the servo system) defines the optimization problem. WOA is integrated with the aim of obtaining optimal controller parameters therefore obtaining a new generation of Takagi-Sugeno-Kang proportional-integral fuzzy controllers. For this, a design method is defined and experimentally validated with the aid of a laboratory nonlinear servo system.

[1]  Spyros G. Tzafestas,et al.  AI-Based Actuator/Sensor Fault Detection With Low Computational Cost for Industrial Applications , 2016, IEEE Transactions on Control Systems Technology.

[2]  Stefan Preitl,et al.  Design of Low-Cost Fuzzy Controllers with Reduced Parametric Sensitivity Based on Whale Optimization Algorithm , 2020, 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

[3]  Stefan Preitl,et al.  Novel Adaptive Charged System Search algorithm for optimal tuning of fuzzy controllers , 2014, Expert Syst. Appl..

[4]  Andrew Lewis,et al.  The Whale Optimization Algorithm , 2016, Adv. Eng. Softw..

[5]  Radu-Emil Precup,et al.  Grey Wolf Optimizer Algorithm-Based Tuning of Fuzzy Control Systems With Reduced Parametric Sensitivity , 2017, IEEE Transactions on Industrial Electronics.

[6]  Prakash Kumar Hota,et al.  Modified whale optimization algorithm for coordinated design of fuzzy lead‐lag structure‐based SSSC controller and power system stabilizer , 2019, International Transactions on Electrical Energy Systems.

[7]  Xin-She Yang,et al.  Community detection in networks using bio-inspired optimization: Latest developments, new results and perspectives with a selection of recent meta-heuristics , 2020, Appl. Soft Comput..

[8]  Subhransu Sekhar Dash,et al.  A modified whale optimization algorithm-based adaptive fuzzy logic PID controller for load frequency control of autonomous power generation systems , 2017 .

[9]  Sylvie Galichet,et al.  Fuzzy controllers: synthesis and equivalences , 1995, IEEE Trans. Fuzzy Syst..

[10]  Radu-Codrut David,et al.  Second Order Intelligent Proportional-Integral Fuzzy Control of Twin Rotor Aerodynamic Systems , 2018, ITQM.

[11]  Eckhard Gauterin,et al.  Fault-tolerant control of wind turbines with hydrostatic transmission using Takagi-Sugeno and sliding mode techniques , 2015, Annu. Rev. Control..

[12]  J. Vascak,et al.  Path planning in dynamic environment using Fuzzy Cognitive Maps , 2008, 2008 6th International Symposium on Applied Machine Intelligence and Informatics.

[13]  Siamak Talatahari,et al.  Upgraded Whale Optimization Algorithm for fuzzy logic based vibration control of nonlinear steel structure , 2019, Engineering Structures.

[14]  Stefan Preitl,et al.  Gravitational search algorithm-based design of fuzzy control systems with a reduced parametric sensitivity , 2013, Inf. Sci..

[15]  Zsolt Csaba Johanyák,et al.  Surrogate Model based Optimization of Traffic Lights Cycles and Green Period Ratios using Microscopic Simulation and Fuzzy Rule Interpolation , 2018 .

[16]  Tshilidzi Marwala,et al.  An adaptive fuzzy predictive control of nonlinear processes based on Multi-Kernel least squares support vector regression , 2018, Appl. Soft Comput..

[17]  Radu-Emil Precup,et al.  An overview on fault diagnosis and nature-inspired optimal control of industrial process applications , 2015, Comput. Ind..

[18]  Hoay Beng Gooi,et al.  A Hybrid Firefly-Swarm Optimized Fractional Order Interval Type-2 Fuzzy PID-PSS for Transient Stability Improvement , 2019, IEEE Transactions on Industry Applications.

[19]  Anthony Mandow,et al.  Using Particle Swarm Optimization for Fuzzy Antecedent Parameter Identification in Active Suspension Control , 2018, 2018 26th Mediterranean Conference on Control and Automation (MED).

[20]  Radu-Emil Precup,et al.  Grey Wolf Optimizer-Based Approach to the Tuning of Pi-Fuzzy Controllers with a Reduced Process Parametric Sensitivity , 2016 .

[21]  Charalampos P. Bechlioulis,et al.  Robust Image-Based Visual Servoing With Prescribed Performance Under Field of View Constraints , 2019, IEEE Transactions on Robotics.

[22]  Pengfei Chen,et al.  An Inter Type-2 FCR Algorithm Based T–S Fuzzy Model for Short-Term Wind Power Interval Prediction , 2019, IEEE Transactions on Industrial Informatics.

[23]  Deepak Kumar Lal,et al.  Grey Wolf Optimizer Algorithm Based Fuzzy PID Controller for AGC of Multi-area Power System with TCPS☆ , 2016 .

[24]  Stefan Preitl,et al.  An extension of tuning relations after symmetrical optimum method for PI and PID controllers , 1999, Autom..

[25]  Igor Skrjanc,et al.  A robust fuzzy adaptive law for evolving control systems , 2014, Evol. Syst..

[26]  Claudia-Adina Dragos,et al.  Combined Model-Free Adaptive Control with Fuzzy Component by Virtual Reference Feedback Tuning for Tower Crane Systems , 2019, ITQM.