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A new design method for adaptive IIR system identification using hybrid particle swarm optimization and gravitational search algorithm

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Abstract

Design of adaptive infinite impulse response (IIR) filter is the process of utilizing adaptive algorithm to iteratively determine the filter parameters to obtain an optimal model for the unknown plant based on minimizing the error cost function. However, the error cost surface of IIR filter is generally nonlinear, non-differentiable and multimodal. Hence, an efficient global optimization technique is required to minimize the error cost objective. A novel hybrid particle swarm optimization and gravitational search algorithm (HPSO–GSA) is proposed in this paper for IIR filter design. The proposed HPSO–GSA updates particle positions through obeying the influence of gravity acceleration in GSA and receiving direction of cognitive memory and social sharing information from PSO by means of coevolutionary strategy. The effect of key parameters on the performance of the proposed algorithm is firstly studied, and the proper parameters in HPSO–GSA are established using five benchmark plants along with the same-order model. The simulation studies have been performed for the performance comparison of eight algorithms such as PSO, GSA, QPSO, DPSO, FO-DPSO, GAPSO, PSOGSA and the proposed HPSO–GSA for unknown IIR system identification with the same-order and reduced-order filters. Simulation results show that the proposed algorithm has advantages over PSO, GSA and other PSO-based variants in terms of the convergence speed and the MSE levels.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China under Grant Nos. 61174032 and 61202473, the National High Technology Research and Development Program of China (863 Program) under Grant No. 2013AA040405, the Specialized Research Fund for the Doctoral Program of Higher Education under Grant No. 20110093130001, the Key Natural Science Research Project of Anhui Province of China under Grant No. KJ2011Z232 and the Fundamental Research Funds for the Central Universities under Grant No. JUDCF13041.

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Authors and Affiliations

  1. Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education, Institute of Electrical Automation, Jiangnan University, Wuxi, 214122, People’s Republic of China

    Shanhe Jiang, Yan Wang & Zhicheng Ji

  2. Department of Physics and Power Engineering, Anqing Normal College, Anqing, 246011, People’s Republic of China

    Shanhe Jiang

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  1. Shanhe Jiang
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  2. Yan Wang
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Correspondence to Zhicheng Ji.

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Jiang, S., Wang, Y. & Ji, Z. A new design method for adaptive IIR system identification using hybrid particle swarm optimization and gravitational search algorithm. Nonlinear Dyn 79, 2553–2576 (2015). https://doi.org/10.1007/s11071-014-1832-0

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