簡易檢索 / 詳目顯示

研究生: 吳坤瑞
Wu, Kun-Jui
論文名稱: 以PSO優化PID控制器參數設計應用於機械手臂之模糊模型
The PSO Optimized PID Controller Parameter Design Applied to Fuzzy Model of Robotic Arm
指導教授: 陳美勇
Chen, Mei-Yung
口試委員: 陳美勇
Chen, Mei-Yung
王俊勝
Wang, Jiun-Shen
張文哲
Chang, Wen-Jer
練光祐
Lian, Kuang-Yow
口試日期: 2024/07/31
學位類別: 碩士
Master
系所名稱: 機電工程學系
Department of Mechatronic Engineering
論文出版年: 2024
畢業學年度: 112
語文別: 中文
論文頁數: 65
中文關鍵詞: Denavit-Hartenberg (D-H) 約定粒子群最佳化演算法機械手臂
英文關鍵詞: Denavit-Hartenberg (D-H) convention, particle swarm optimization (PSO), Robot Manipulator
研究方法: 實驗設計法
DOI URL: http://doi.org/10.6345/NTNU202401767
論文種類: 學術論文
相關次數: 點閱:59下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 本文使用 Denavit-Hartenberg (D-H) 約定推導六自由度機械手臂的運動模型,包括運動學與動力學。為了克服運動模型的高度非線性問題,我們透過了 T-S 模糊系統來建立非線性系統之線性化模型。並利用此線性化模型,我們可以通過平行分佈式 PID 控制器來控制機械手臂。
    根據連續軌跡的要求、各手臂的長度以及關節旋轉的角度限制,運動形式的設計需要擬合機器人手臂的運動模型。機械手臂系統中的 PID 控制器其參數係通過粒子群最佳化演算法(PSO)求得的。根據系統轉移函數,優化後的控制器參數可以在機械手臂運轉時抵抗系統的不確定性,使機械臂在運作時有能更高效且更平穩。
    利用 Matlab 中的 Simulink 對系統進行模擬,分析範圍包括定點跟踪和軌跡跟踪。與傳統的 PID 控制器相比,結果顯示所提出的控制器參數具有更小的穩定性誤差且有較佳的調和性與較小的振動,並依此參數操作機械手臂觀察手臂之運動情形,其結果為手臂運作很均勻無抖動現象。

    This paper uses the Denavit-Hartenberg (D-H) convention to derive the motion model, including the kinematics and dynamics, of the 6-DOF robotic arm. In order to overcome the highly nonlinear issue of the motion model, we linearize the nonlinear system by T-S fuzzy modeling.
    Based on the linearized model, we can control the robotic arm through a parallel distributed PID controller. According to the requirements of the continuous trajectory, the length limits of each arm, and the angle limits of the joint rotation, the design of motion form needs to fit the motion model of the robot arm.
    The parameters of the PID controller are found by the particle swarm optimization (PSO). According to the system transfer function, the controller with the optimized parameters can resist the uncertainty of the system, and make the robot arm move more efficiency and smoothly.
    The system’s simulated in Matlab is used to simulate the system, and the analysis scope includes fixed-point tracking and trajectory tracking. Compared with the traditional PID controller, the results show that the proposed controller parameters have smaller stability errors, better harmonic and smaller vibration and operate the robotic arm according to these parameters to observe the movement of the arm,The result is that the arm operates evenly without shaking.

    摘要 I Abstract II 誌謝 III 目錄 IV 表目錄 VI 圖目錄 VII 第一章 緒論 1 1.1前言 1 1.2文獻回顧 2 1.3研究動機與目的 7 1.4 論文架構 8 第二章 本研究之相關理論基礎 10 2.1 PSO演算法與控制器參數調整之關係 11 2.2 機器手臂D-H座標系統之定義 15 2.3 機械手臂正向運動學 18 2.4 逆向運動學 24 2.5模糊控制系統 27 第三章 機械手臂系統控制器設計及穩定分析 30 3.1模糊系統控制(T-S Fuzzy Control System) 30 3.2 PID控制器設計(PID Controller Design) 32 3.3 利用Lyapunov理論分析系統之穩定 34 3.4系統之穩定性分析 39 第四章 實驗設備 40 4.1機械手臂硬體構造 40 4.2系統之驅動器 41 4.3系統使用之運動控制卡 43 4.4系統之資料擷取卡 44 4.5運動控制之系統軟體 44 第五章 系統模擬與實驗結果 46 5.1 PSO演算找最佳解之案例 46 5.2以PSO演算找最佳解方式求PID控制器增益 47 5.3 模糊控制系統之模擬及應用 49 5.4以PID控制器用於機械手臂之運動控制 51 5.5 機械手臂執行畫圖之運作 60 第六章 結論與未來展望 63 參考文獻 64

    Hamza Khan. Saad Jamshed Abbasi, and Karam Dad Kallu, “Robust Control Design of 6-DOF Robot for Nuclear Power Plant Dismantling,” 2019 International Conference on Robotics and Automation in Industry (ICRAI) Year: Publication Year: 2019,Page(s):1 - 7.
    Alam, M.S. and Tokhi, M.O.,“Hybrid Fuzzy logic control with genetic optimization for a single link flexible manipulator”, Journal of Engineering Applications of Artificial intelligence 2,pp. 858- 873,2008.
    Federico Marinia, Beata Walczakb, “Particle swarm optimization (PSO). A tutorial”, Chemometrics and Intelligent Laboratory Systems 149 (2015) 153–165 Volume 149, Part B, 15 December 2015, Pages 153-165
    Y. Guangyou, "A Modified Particle Swarm Optimizer Algorithm," 2007 8th International Conference on Electronic Measurement and Instruments, Xi'an, China, 2007, pp. 2-675-2-679, doi: 10.1109/ICEMI.2007.4350772.
    O.Djaneye-Boundjou, X. Xu and R.Ordóñez, "Automated particle swarm optimization based PID tuning for control of robotic arm," 2016 IEEE National Aerospace and Electronics Conference (NAECON) and Ohio Innovation Summit (OIS), Dayton, OH, USA, 2016, pp. 164-169, doi: 10.1109/NAECON.2016.7856792.
    Kennedy and R. Eberhart, "Particle swarm optimization,"Proceedings of ICNN'95 - International Conference on Neural Networks, Perth, WA, Australia, 1995, pp. 1942-1
    John J. Craig, “Introduction to Robotics: Mechanics and Control,” London ,Pearson Education International, 2005.
    Ya Lei Sun and Meng Joo Er, "Hybrid fuzzy control of robotics systems," in IEEE Transactions on Fuzzy Systems, vol. 12, no. 6, pp. 755-765, Dec. 2004, doi:10.1109/TFUZZ.2004.836097948 vol.4, doi: 10.1109/ICNN.1995.488968.
    Claudio Urrea , John Kern and Johanna Alvarado,” Design and Evaluation of a New Fuzzy Control Algorithm Applied to a Manipulator Robot”, Journals Applied Sciences Volume 10 Issue 21DOI:10.3390/app10217482
    Nowaková, J.; Pokorný, M.; Pieš, M. Conventional controller design based on Takagi–Sugeno fuzzy models. J. Appl. Log. 2015, 13, 148–155. DOI:10.1016/j.jal.2014.11.008.
    K. Tanaka, T. Hori and H. O. Wang, "A fuzzy Lyapunov approach to fuzzy control system design," Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148), Arlington, VA, USA, 2001, pp. 4790-4795 vol.6, doi: 10.1109/ACC.2001.945740.
    Nasr M. Ghaleb and Ayman A. Aly,” Modeling and Control of 2-DOF Robot Arm”, International Journal of Emerging Engineering Research and Technology Volume 6, Issue 11, 2018, PP 24-31 ISSN 2349-4395 (Print) & ISSN 2349-4409.
    Chung-Shi Tseng, Bor-Sen Chen and Huey-Jian Uang, "Fuzzy tracking control design for nonlinear dynamic systems via T-S fuzzy model," in IEEE Transactions on Fuzzy Systems, vol. 9, no. 3, pp. 381-392, June 2001, doi: 10.1109/91.928735.
    L. -W. Huang, C. -Y. Cheng and G. -R. Yu, "SOS-based design of fuzzy tracking controller for a two-link robot arm," Proceedings 2011 International Conference on System Science and Engineering, Macau, China, 2011, pp. 437-442, doi: 10.1109/ICSSE.2011.5961943.
    .M. I. El-Hawwary, A. L. Elshafei, H. M. Emara and H. A. A. Fattah, "Adaptive Fuzzy Control of the Inverted Pendulum Problem," in IEEE Transactions on Control Systems Technology, vol. 14, no. 6, pp. 1135-1144, Nov. 2006, doi: 10.1109/TCST.2006.880217
    L. -W. Huang, C. -Y. Cheng and G. -R. Yu, "SOS-based design of fuzzy tracking controller for a two-link robot arm," Proceedings 2011 International Conference on System Science and Engineering, Macau, China, 2011, pp. 437-442, doi: 10.1109/ICSSE.2011.5961943.

    無法下載圖示 電子全文延後公開
    2025/08/12
    QR CODE