以人工智慧建立精密平台定位控制器

Precision Servo Design Based upon Artificial Intelligent Algorithm

陳潔安(Jie-An Chen)

指導教授 ： 顏家鈺

國立臺灣大學/工學院/機械工程學研究所/碩士(2019年)

https://doi.org/10.6342/NTU201901955

摘要

本論文比較在精密量測平台上，使用最小積分誤差的方式求控制器參數和使用強韌控制 H ∞ 控制器的系統性能。其中尋找最小誤差積分的方法使用粒子群最佳化（Particle Swarm Optimization, PSO）演算法，並提出使用強化式學習搭配粒子群最佳化的方式，來避免系統停滯在區域最佳解。
本系統使用線掃描相機來掃描晶圓，其中相機掃描方向為 Y 方向，故 X 方向需要精準的定位精度而 Y 方向在勻速區段需有平穩的移動速度，因此在控制器架構上，X 軸、Y 軸分別使用位置控制和速度控制，位置控制能使系統有較高的定位和跟蹤精度；而速度控制使系統在勻速區段能有較小的速度誤差。
控制器參數設計方法有以下兩種方式，一為最小誤差積分，其準則採用 IAE、ITAE、ISE 和 ITSE。二為使用由 Tsai 所提出的以鏈散射描述法（Chain Scattering Description, CSD）的架構來計算 H-infinity 控制器，此方法能以較簡單的數學計算並直觀地推導出 H-infinity 控制器。並將此上述兩種控制器設計方式所計算出的參數，套用到實際系統做單軸定位和雙軸同動實驗，依據實驗結果比較系統性能。

關鍵字

粒子群最佳化 ； 強化式學習 ； 強韌控制 ； 鏈散射描述法

並列摘要

This thesis compares the system performance of wafer inspection stage by using two controller designing method, one is tuning the control parameters by optimization algorithm to minimize the integral of the error, the other is using H-infinity controller. Particle Swarm Optimization(PSO) is used to tuning the controller parameters and in order to make the algorithm not to fall into local optimum, this thesis proposed to integrate reinforcement learning into the PSO.
In the wafer inspection process, the line scan camera is used. The camera scan direction is y-direction, therefore x-direction need to have high positioning accuracy and y-direction need to have smooth motion speed during the uniform speed region. Due to the above reasons, position control which can make the system have high positioning and tracking accuracy is applied in x-axis; and velocity control which can make the system have small velocity error during the uniform speed region is applied in y-axis.
There are two controller designing methods which is used in this thesis. One is minimizing the integral of the error. The system performance criterions are IAE Integral of the absolute value of the error), ITAE(Integral of the time weighted absolute value of the error), ISE(Integral of the square value of the error) and ITSE(Integral of the time weighted square value of the error). These criterions are used as PSO fitness function. The other method is robust H-infinity control applied the CSD(Chain Scattering description) structure calculating the H-infinity controller. This calculate method is proposed by Tsai, and it can simplified the complex H-infinity calculation and intuitively derive the mathematical formulation. The system performance is compared and presented in this thesis by applied these two controller to the wafer inspection stage and experiment the single axis and dual-axis synchronize motion.

並列關鍵字

Particle swarm optimization ； Reinforcement learning ； Robust Control ； Chain Scattering Description

參考文獻

[1] Tsai, Mi-Ching, and Da-Wei Gu, Robust and optimal control: a two-port framework approach, Springer Science & Business Media, 2014.

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[3] R. Mendes, "Population Topologies and Their Influence in Particle Swarm Performance (PhD thesis)," in Universidade do Minho, 2004.

[4] Shahrokhi, Mohammad, and Alireza Zomorrodi, "Comparison of PID controller tuning methods," in Department of Chemical & Petroleum Engineering Sharif University of Technology, 2013.

[5] Sahu, Rabindra Kumar, et al, "Teaching learning based optimization algorithm for automatic generation control of power system using 2-DOF PID controller," International Journal of Electrical Power & Energy Systems 77, pp. 287-301, 2016.