臺灣博碩士論文加值系統

本論文主要目的是研究當車體受到外來路面的干擾時能即時改變主動式懸吊系統的位置並追蹤控制之相關問題，以達到主動式懸吊系統之操控目的。本文提出了二種控制架構，一為PID控制系統，另一為類神經網路控制系統，後者已達到最佳的控制功能。類神經網路是由諸多神經元連結而成的網路系統，而且具有線上學習的功能與鑑別的能力，所以提出了類神經網路控制器，其中學習過程是利用倒傳遞演算法調整連結權重值，使得懸吊系統的輸出與目標值之間的誤差減小，而控制器之主要目的是控制主動式懸吊系統的輸出位置，以降低誤差，改善車輛的橫向平穩性。
本論文進一步以MATLAB/Simulink軟體來建構控制系統程式並進行動態模擬，由模擬結果可以發現，本文所提出之二種控制架構對於車體振動量和加速度均有明顯的抑制效果。最後利用本文所建構的1/4T主動式懸吊系統實驗裝置，驗證了主動式懸吊不論是在追蹤性能的提昇或是汽車乘坐舒適性的改善均具有顯著的效果。

The main purpose of this thesis is to research on the car suspension system subjected to different road profiles and achieve the purpose of the control of active suspension system. Two controllers are utilized in this thesis, one is PID control system and the other is neural networks. The latter can achive the best results. Neural networks is a control system that connected by neuros. And it has abilities of on-line learning and identification. The learning process used EBP to adjust weighting. It decrease to the error of active suspension system. The purpose of controler is to control output position of active suspension system to decrease errors and improve steady of vehicle.
This thesis used the MATLAB/Simulink to design moden control system and to do dynamic simulation. From the result of simulations, we can find that the two control theory have obvious inhibition about body deflection and acceleration. Finally, a quarter vehicle active suspension test rig is constructed. The experimental results show that the active suspension system exhibits superior performance of force tracking and significant improvement of the ride quality.

中文摘要 ------------------------------------------------------------------------------- i
英文摘要 ------------------------------------------------------------------------------- ii
誌謝 ------------------------------------------------------------------------------- iii
目錄 ------------------------------------------------------------------------------- iv
表目錄 ------------------------------------------------------------------------------- vi
圖目錄 ------------------------------------------------------------------------------- vii

一、 緒論------------------------------------------------------------------------ 1
1.1 研究背景------------------------------------------------------------------- 1
1.2 研究動機------------------------------------------------------------------ 5
1.3 研究目的------------------------------------------------------------------ 6
1.4 文獻回顧------------------------------------------------------------------ 6
1.5 研究的方向與論文架--------------------------------------------------- 7

二、 主動式懸吊系統之架構與數學模------------------------------------ 8
2.1 主動式懸吊系統的描述------------------------------------------------ 8
2.2 主動式懸吊系統的主要系統架構及其方程------------------------ 10
2.2.1 液壓伺服位置控制系統------------------------------------------------ 10
2.2.2 懸吊系統運動方程式--------------------------------------------------- 12
2.2.3 主動式懸吊系統之PID控制器設計方塊圖------------------------ 14
2.4 實驗設備------------------------------------------------------------------ 15
2.4.1 懸吊機構部份------------------------------------------------------------ 18
2.4.2 電控系統部分------------------------------------------------------------ 19
2.4.3 懸吊系統各種感測器信號處理與量測------------------------------ 21
2.5 MATLAB/Simulink與ADAMS/VIEW連結----------------------- 23
2.5.1 以ADAMS建構1/4 T主動式懸吊模型---------------------------- 23
2.5.2 ADAMS與MATLAB/Simulink 之連結介面---------------------- 24

三、 控制理論介紹------------------------------------------------------------ 26
3.1 PID控制理論------------------------------------------------------------- 26
3.1.1 PID控制------------------------------------------------------------------- 26
3.1.2 PID控制的調整法------------------------------------------------------- 28
3.1.3 臨界靈敏度調整法------------------------------------------------------- 29
3.2 類神經網路控制理論---------------------------------------------------- 30
3.2.1 神經元模型---------------------------------------------------------------- 30
3.2.2 類神經網路架構---------------------------------------------------------- 34
3.2.3 類神經網路的學習法則------------------------------------------------- 37
3.2.4 類神經網路控制器架構------------------------------------------------- 39
3.2.5 傳導神經網路------------------------------------------------------------- 42
3.2.6 倒傳遞類神經網路的學習演算法------------------------------------- 44

四、 PID控制器設計之模擬與實驗結果---------------------------------- 52
4.1 簡介------------------------------------------------------------------------- 52
4.2 實驗台各項參數數據---------------------------------------------------- 53
4.3 1/4 T主動式懸吊系統模擬--------------------------------------------- 54
4.4 動式懸吊系統之PID控制器設計方塊圖---------------------------- 56
4.5 1/4 T主動式懸吊系統實驗--------------------------------------------- 60
4.6 MATLAB/Simulink與ADAMS/VIEW連結模擬結果------------ 64

五、 纇神經網路控制器設計之模擬與實驗結果------------------------ 67
5.1 簡介------------------------------------------------------------------------ 67
5.2 主動式懸吊系統之類神經網路控制器設計方塊圖--------------- 67
5.3 1/4 T主動式懸吊系統實驗-------------------------------------------- 71

六、 結論與未來展望---------------------------------------------------------- 76
6.1 結論------------------------------------------------------------------------- 76
6.1.1 模擬分析比較------------------------------------------------------------- 76
6.1.2 實驗分析比較------------------------------------------------------------- 79
6.1.3 結果分析------------------------------------------------------------------- 83
6.2 未來展望------------------------------------------------------------------- 83

參考文獻 --------------------------------------------------------------------------------- 85
自傳 ------------------------------------------------------------------------------- 86

1. Appleyard, M. and Wellstead, P. E. 1995, “Active suspension: some background,” IEE Proc. Control Theory Appl., vol. 142. No 2, pp. 123-128.
2. Andrew A. and Hedrick, J. K. 1995,“Nonlinear adaptive control of active suspensions,” IEEE Transactions on control systems technology, vol. 3, No 1, pp. 94-101.
3. Rajamani, R. and Hedrick, J. K. 1995, “Adaptive observers for active suspensions: theory and experiment,” IEEE Transactions on Control Systems Technology, vol. 3. No 1, pp. 86-93.
4. Ting, C. S. and LI, T. H. S. 1995, “Design of fuzzy controller for active suspension system,” Mechatronics, vol. 5, No. 4, pp. 365-383.
5. M. Sunwoo, K.C. Cheok and N.J. Huang,“Model Reference Adaptive Control for Vehicle Active Suspension Systems,”IEEE Trans. on Industrial Electronics,Vol.38, No.3, pp.217-222, June1991.
6. Yi-Pin Kuo & Tzuu-Hseng S. Li, “GA-Based Fuzzy PI/PD Controller for Automotive Active Suspension System”, IEEE Transactions on Industrial Electronics , Vol.46 ,No.6,pp1051-1056,Decemeber 1999.
7. Supavut Chantranuwathana & Huei Peng, “Adaptive Robust Control for Active Suspensions”, Proc. of the 1999 American Control Conference, pp.1702-1706.
8. M.V.C Rao and V. Prahlad,“A Tunable Fuzzy Logic Controller for Vehicle-active Suspension System,”Fuzzy Sets and Systems,Vol.85.pp. 11-21,1997.
9. Andrew A. and Hedrick, J. K. 1995,“Nonlinear adaptive control of active suspensions,” IEEE Transactions on control systems technology, vol. 3, No 1, pp. 94-101.
10. Chantranuwathana, S. and Peng, H. 1999, “Force tracking control for active suspensions theory and experiments,” IEEE Proc. Conference on Control Appl. pp. 442-447.
11. Kim, C. and Ro, P. I. 1997, “A sliding mode controller for vehicle active suspension systems with non-linearities,” Imeche Proc. Instn. Mech. Engrs. vol. 212. Part D, pp. 79-92.
12. 呂紹灝、陳文良、葉莒，“半主動懸架系統之避震器限制與系統模擬”，博士論文，國立清華大學 動力機械工程學系，中華民國八十八年六月。
13. 趙紘慶、黃緒哲，“車輛主動式懸吊之控制系統之研究”，國立臺灣科技大學機械工程技術研究所，碩士學位論文，中華民國八十七年六月。
14. 林威成、黃緒哲，“主動式車輛懸吊之控制器設計”，國立臺灣科技大學機械工程技術研究所，碩士學位論文，中華民國八十九年六月。
15. R. A. Williams,” Automotive Active Suspensions Part 1: basic principles,” ImechE Proc. Instn. Mech. Engrs., Vol. 211. Part D , 415-426, 1997.
16. Andrew Alleyne and J. Karl. Hedrick, “Nonlinear Adaptive Control of Active Suspensions,” IEEE Transactions on control systems technology, vol. 3, No 1. 94-101, 1995
17. H. M. Chen, J. P. Su, J. C. Renn,” Electrohydraulic Position Control Using Soft Switching Strategy in the Boundary Layer,” Automatic Control Conference, December, 2002.
18. Renn, J. C. 1997, “A New approach to synthesize the feedback gains of state-space controller for a servo hydraulic positioning system,” Journal of Control systems and technology, vol. 5, No. 1, pp. 51-59.
19. Merrit, H.E., 1967, “ Hydraulic control system,” (John Wiely).
20. Watton, J. 1989, “Fluid power systems,” (Prentice Hall).
21.任志強，伺服液氣壓學，上課講義，國立雲林科技大學機械所，1998。
22. 張記函，汽車懸吊避震器於規則路面之舒適性分析，國立雲林科技大學碩士論文，2003。
23. 張碩, 1997, 自動控制系統,鼎茂圖書出版有限公司。
24. T. Fukuda and T. Shibata, “Theory and application of neural networks for industrial control system,” IEEE Transaction on Industrial Electronics,pp.472-489,1992.
25. 林法正、魏榮宗、段柔勇，超音波馬達之驅動與智慧型控制，滄海書局，1999。
26. 陳堃峯，應用模糊類神經網路於壓電致動器之精密定位控制研究，國立東華大學電機工程研究所碩士論文，2004。
27. S. Haykin, Neural Network: A Comprehensive Fundation, New-York, Prentice Hall Intl,1999.
28. 張斐章、張麗秋、黃浩倫，類神經網路，東華書局，2003。
29. D. Psaltis, A. Sideris, and A. A. Yamamura, “A multilayered neural network controller,” IEEE Control System Magazine, pp. 17-21,1988.
30. Real-time workshop: for use with simulink, ver. 3.0, user’s guide, the math works Inc., 1999.