【作者】 王凯；

【导师】 孔峰；

【作者基本信息】 广西大学 ， 控制理论与控制工程， 2006， 硕士

【摘要】 近年来，以模糊控制和神经网络控制相结合的软计算技术获得了广泛关注。模糊控制具有响应速度快、鲁棒性强的优点，在系统阶跃响应的暂态阶段，模糊控制能够很快减小误差。但是，单纯的模糊控制往往难以得到满意的稳态精度。本文借鉴切换控制理论，提出了新型的“模糊切换”方法，设计了与神经网络并联的模糊控制器，以解决具有不确定性的复杂系统的控制问题。 一般混合控制器根据误差精确量为阈值进行切换动作。这种常规切换算法简单，易于编程或硬件实现。但是在切换时刻却要保证两个控制器输出大体相等，这对闭环控制是很高的要求。若不能满足则会在切换点处出现振荡并降低控制器的鲁棒性。本文针对这种情况提出的模糊切换的概念，使用误差及其变化的模糊数作为切换阈值，从而使两种不同控制器可以消除切换时因不同控制器输出差异导致的跳变或时滞，以更好的完成切换。 针对工业中常见的直流电机系统进行了仿真试验，仿真结果验证了该算法的有效性，表明这种控制方案能够有效地提高系统的鲁棒性，并且具有很好的适应性和鲁棒性。更多还原

【Abstract】 The combination of fuzzy and ANN control as soft computing has gained widely concern in recent years. A superior feature of fuzzy control is the improvement of the transient characteristic of control performance and control with excellent robustness can be easily realized. However, a sole controller of fuzzy algorithm is hard to attain satisfactory accuracy in the steady state. Therefore, a hybrid controller of paralleled FNN is designed with fuzzy and FRNC served as subcontrollers. The fuzzy switching is used to synthesise the two algorithms to form a feasible method for uncertain system control.Moreover, smooth control during switching is guaranteed by executing the change using fuzzy inference. The concept of fuzzy switching membership function is introduced to complete the new switching method. Fuzzy variables of error and error change are used as the switching criterion instead of the accurate value. The new switching method avoided the bottleneck of forcing two controller outputs equal to each other at the switching point, and therefore a more smooth and robust control effect is obtained.Simulation is performed to the DC motor, which is widely used in the industry. The result demonstrated that the algorithm proposed could yield satisfactory response to sharp reference signal step change and the algorithm is both feasible and effective.更多还原