【作者】 李泉；

【导师】 侯国莲；

【作者基本信息】 华北电力大学（北京） ， 控制理论与控制工程， 2004， 硕士

【摘要】 本文研究了新型智能控制系统及其在热工过程控制中的应用。首先，提出了两种智能控制器设计方法：具有参数自校正功能的模糊PID控制器；具有规则库自调整功能的模糊控制器。其次，针对热工对象存在大惯性、大迟延问题，设计了一种基于性能指标的规则库可优化的模糊控制器；针对热工对象存在大范围变工况问题，设计了一种适合于全工况范围变化的智能串级控制系统。再次，基于模糊控制和滑模控制的特点，对模糊系统的学习算法进行了研究，提出了一种后件参数在线自学习的模糊控制算法。并同时将上述算法分别应用于火电厂热工控制中。最后，在上述自学习模糊控制算法中，引入论域伸缩因子，研究并设计出一种适合多变量控制系统的变论域模糊控制算法，运用Lyapunov方法证明了算法的收敛性，并应用于火电厂单元机组协调控制系统中。通过大量仿真实验，证明了本文所提出的控制算法的有效性。更多还原

【Abstract】 The Intelligent control system and its application in thermal process control are researched in this paper. Firstly, two intelligent control algorithms are proposed: a self-tuning fuzzy PID controller and a fuzzy controller with fine-tuning rule base. Secondly, a fuzzy controller based on performance index is designed, which is suitable for the object with large inertia and delay; considering the variable model of the object in the different set point, a intelligent cascade control system is presented. Thirdly, the on-line learning algorithm for the output parameter of fuzzy slide mode controller is given, simultaneously, above methods are respectively applied to the process control of unit in power plant. Finally, a fuzzy control strategy with variable universe for MIMO systems is designed by adding a flex gene to the learning algorithm. The convergence of the learning algorithm is proved through Lyapunov method, and it is applied to the coordinated control system for the boiler-turbine unit. A great of simulation results show the advantages of these presented control strategies in this paper.更多还原