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Temperature control by chip-implemented adaptive recurrent fuzzy controller designed by evolutionary algorithm
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DOI：10.1109/TCSI.2005.854138.png)
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Abstract
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Online adaptive temperature control by field-programmable gate array (FPGA)-implemented adaptive recurrent fuzzy controller (ARFC) chip is proposed in this paper. The RFC is realized according to the structure of Takagi-Sugeno-Kang (TSK)-type recurrent fuzzy network. Direct inverse control configuration is used. To design RFC offline, evolutionary fuzzy controller using the hybrid of the Simplex method and particle swarm optimization (SPSO) is proposed. In SPSO, each RFC corresponds to a particle, and all the free parameters in RFC are optimally searched. We use the PSO to find a good solution globally, and the incorporation of the Simplex method helps find a better solution around the local region of the best solution found by PSO so far. Then, online adaptive temperature control with ARFC chip implemented by FPGA is proposed. In the ARFC chip, the consequent parameters of all rules are all tuned online using gradient descent. To verify the performance of the ARK chip, experiments on a water bath temperature system are performed.
Keywords:
direct inverse control
fuzzy chip
fuzzy control
neural fuzzy networks
particle swarm optimization (PSO)
Simplex method
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