SELF-ADAPTIVE NEURON PID CONTROL IN EXHAUST TEMPERATURE OF MICRO GAS TURBINE

摘要：

Mathematical model scheme of exhaust temperature control in micro gas turbine is given out. To obtain better performance, a self-adaptive neuron PID control is applied to the exhaust temperature control in this paper. The neuron model and learning strategy are given. The effectiveness and efficiency of the proposed control strategy is demonstrated by applying it to the exhaust temperature control. The different learning velocity and neuron proportion of self-adaptive neuron PID control are simulated to analyze the control performance. It is found that the neuron proportion in self-adaptive neuron PID control is the most sensitive parameter, the learning velocities of proportion and integrator affect the rapidity of response, overshoot and static error, while the learning velocity of differentiator affects relatively little to the control performance. The simulations show that the dynamic responses of the exhaust control system can be effectively improved and the robustness of the proposed controller is better than that of the PID controller.

关键词： Neuron PID control Self-adaptive Ezhaust temperature control Micro gas turbine

作者: JIANG-JIANG WANG YOU-YIN JING CHUN-FA ZHANG

作者单位: School of Energy and Power Engineering, North China Electric Power University, Baoding 071003, China School of Energy and Power Engineering, North China Electric Power University, Baoding 071003,China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 2125-2130

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）