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Article type: Research Article
Authors: Agnihotri, S.P.a; * | Waghmare, Laxman Madhavraob
Affiliations: [a] Electronics and Telecommunication Engineering, Gokhale Education Society R H Sapat college of Engineering Research studies and Management, Nashik, Maharashtra, India | [b] SGGS Institute of Engineering and Technology, Vishnupuri, Nanded, India
Correspondence: [*] Corresponding author. S.P. Agnihotri, Assistant Professor, Electronics and Telecommunication Engineering, Gokhale Education Society R H Sapat college of Engineering Research studies and Management, Nashik, Maharashtra, India. Tel.: +91 7588306244; E-mail: [email protected].
Abstract: This paper proposed a cuckoo search (CS) algorithm and self reunion multiple regression (SRMR) method based optimal tuning of proportional integral derivative (PID) controller with high order time delay system. The main part of this projected technique is in hybridizing SRMR with CS algorithm and so enhanced searching ability, random reduction and mitigated difficulty can be achieved. The main goal of this paper is to acquire the optimal control parameter of the PID controller depend on the outcome deviation of the higher order time delay system. In this projected technique is used to derive the SRMR function from the higher order system output parameters. Here, the CS algorithm depends on the least square error (LSE) minimization function is used to optimize the SRMR coefficients. The projected technique is helps to achieve the best fit parameter of the higher order system and improving the consistency of the system. The projected technique is applied in the MATLAB/Simulink platform and examined under various types of higher order time delay systems. The efficiency of the projected technique is proved by the comparative analysis with the existing techniques. The differentiation results consistently prove the efficiency of the projected technique and verified its potential to resolve the related problems.
Keywords: SRMR, CS, LSE, PID controller, higher order time delay system
DOI: 10.3233/IFS-162195
Journal: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 3, pp. 1287-1297, 2016
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