本論文以自我調整PID控制器的增益參數方法為主要架構，並將自調式PID控制器以調整方法產生的修正增益參數特性，區分成區域性調整和全域性調整兩種型式，作為本論文的兩個主要主題。第一個主題，透過模擬探討有關使用原本的自調式類神經PID控制器方法的問題，由於使用雙彎曲函數對PID增益參數的修正範圍特性只能區域性的修正參數，因此考慮到這一項缺點，本論文提出了可以全域性的修正PID增益參數方法，作為本文第二個主題。第二個主題，由於許多函數可由二次型式函數近似，基於這個理論，我們利用了梯度最佳化觀念的特性再加上滑動模式控制的穩定概念，來設計出適應性控制所需要的適應法則，有別於一般使用李亞諾夫分析方法求得的方式。我們並透過混沌系統和倒單擺系統來進行模擬實驗，並由實驗結果可以看出本文所提出的方法也有不錯的效果，並且能達到全域性調整的目的。

This research is based on the self-tuning PID control method for three PID control gains adjustment. In this study, the self-tuning PID control method is classified into two types as local tuning and global tuning. The first one is through simulation to discuss the problem of using the original self-tuning neural PID approach. Due to the use of sigmoid function, the modification range of parameters is only local. In view of this drawback, we proposed a novel self-tuning method for PID control gains adjustment which can have global modification for those parameters. This approach utilizes the gradient optimum concept property and sliding mode stable idea to design the adaptive laws. This approach is different from the general way of designing the adaptive laws which is usually obtained by using the concept of the Lyapunov analysis method. Furthermore, an inverted pendulum system and an uncertain chaotic system are employed to demonstrate the control performance of the proposed approach. Good efficiency is shown in our simulation results.

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