An Optimizing Parameter-Tuning of Multi-Loop Controllers for Boiler Combustion Process

Hong He and Yonghong Tan


Parameter tuning, PID controller, immune evolutionary algorithm, boiler combustion


The combustion process of boiler is a complex and nonlinear system with multiple-loop. Although the traditional PID control strategy has been widely used in boiler combustion systems, it is still difficult to achieve satisfactory parameter-tuning due to the complexity of the system. In this paper, the PID controllers adjusted by an adaptive immune evolutionary algorithm (AIEA) is proposed to tune the parameters of the PID controller automatically in order to obtain optimizing control performance of the system. In this scheme, the AIEA method is implemented to minimize the hybrid optimization indexes so as to obtain fast, stable and accurate tracking results with limited control efforts. The simulation results show that the proposed method has derived better control performance than that of the PID control scheme with the parameter-tuning by the standard genetic algorithm (SGA) and the PID control strategy tuned by the Ziegler –Nichols method.

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