自适应加热器要点分析.docx

自适应加热控制器 自适应加热控制器 题 目 自适应加热控制器 系 别 专 业 班 级 学生姓名 学 号 指导教师 2015年4月  PAGE \* MERGEFORMAT II  PAGE \* MERGEFORMAT III 自适应加热控制器的设计 摘要：在控制理论和技术飞跃发展的今天，自适应控制由于其结构简单、稳定性能好可靠性高等优点而被广泛应用。然而在实际的工业过程中，许多被控过程机理复杂，具有高度非线性。这就要求在自适应控制中，不仅自适应参数的整定不依赖于对象数学模型，并且自适应参数能在线调整，以满足实时控制的要求。自适应自适应自适应控制将是解决这一问题的有效途径。利用神经网络具有自学习、自组织、联想记忆和并行处理等功能和对??复杂系统控制可以达到满意效果的优势，提出了具有自学习和自适应能力的自适应来构成自适应加热控制器的策略。这种自适应构成的控制器不仅结构简单，且能适应环境变化，有较强的鲁棒性。使自适应自适应控制达到最优。其仿真结果表明：该控制器与典型的自适应控制器相比，系统输出能够很好地跟踪参考模型的输出显著提高了系统的动态响应性能。 关键词：自适应 自适应控制 自适应 Single Neuron Adaptive PID Controller Design AbstractIn: the raPID development of control theory and technology nowaday, PID control has been widely used because of its simple structure, stable performance and high reliability. However, in actual industrial processes, many complex mechanism controlled process has highly nonlinear.This requires the PID control, PID parameter setting not only do not rely on mathematical models, and the PID parameters can be adjusted on line to meet the requirements of real-time control. Single neuron adaptive PID control will be an effective way to solve this problem. Using neural network self-learning, self-organization, associative memory and parallel processing features and control of complex systems can achieve satisfactory results, this paper proposed a self-learning and adaptive capacity of single neurons to form the single neuron adaptive PID control strategy. These neurons constitute the controller not only simple in structure, and can adapt to environmental changes, have stronger robustness. Adaptive PID control to optimal. The simulation results show that the controller, compared with the typical PID controller, the system output can track the reference model very well, the output of the system significantly improved dynamic response. Key