西元1999年9月21日，台灣發生1935年以來規模最大的地震，造成超過2300人的死亡及82,000棟房屋受損，造成之傷亡歷來少見。近年來國內經濟蓬勃發展，重大工程建設及房屋建築的數量亦直線上升，此等結構物若在地震中損毀，對生命、財產之損失乃至國家經濟及社會之衝擊將難以估計，因此，一追踪定位且穩定之振動平台和主動質量阻尼器於樓層結構之減振控制是必需的。
傳統伺服系統之定位追踪控制乃是採用固定增益之比例-積分控制器，然而在不同的操作條件下，並非都能達到良好的定位追踪效果。本文提出一類神經網路分類控制器，以增加控制器之強健性。此法乃將誤差範圍分類，經由倒傳遞類神經網路學習，以直接實驗法產生適當之控制訊號輸入系統，進而達成定位追踪之目標。此法之訓練簡易且系統不須識別，亦無須模糊化與解模糊化之過程，可即時達到追踪特定曲線。為了提昇控制器之性能，結合遺傳基因演算法，以產生更強健之控制訊號輸入，從系統模擬和實際實驗上都顯示所提出的類神經網路分類控制器，不論在上升時間、定位精度及強健性上，與傳統的固定增益之比例-積分控制器、類神經網路控制器或模糊控制器比較下，有更優異之定位追踪控制效果。
在振動平台的應用方面，本文亦發展一智慧型控制器—類神經模糊系統，結合類神經網路和模糊邏輯系統之優點，應用於樓層結構系統之減振控制上，從系統模擬和實際實驗上都顯示所提出的類神經網路分類控制器與類神經模糊控制器，在不同的激擾環境下，均能有效達到樓層結構之振動抑制效果。

On September 21, 1999, Taiwan was slammed by Taiwan's biggest quake since 1935. The magnitude 7.6 tremor with its epicenter in central Nantou County killed more than 2,300 persons and damaged 82,000 housing units. With the trend toward taller and more flexible building structures, the use of vibration control devices, passive as well as active, as means of structural protection against strong wind and earthquakes have received significant attention in recent years. A mass-damper shaking table system has been considered as means for vibration suppression to external excitation and disturbances. Tracking accuracy and stability are thus highly desirable.
To increase the robustness of conventional fixed-gain PI controllers, a neural classifier controller based on neural network is proposed in this dissertation to generate the control gain for desired performance. The direct experiment method is adopted to determine the control gains for better performance index. No explicitly system identification of the plant dynamics, no membership function and thus no fuzzification-defuzzification operation are required. For effective control performance, a neural classifier controller with genetic algorithm is also developed. From simulations and experimental results, the neural classifier is demonstrated to overcome the robustness problem of the fixed-gain PI controller and follow with the high-performance abilities of the neural network and fuzzy controller. Experimental results show that the neural classifier is effective for position tracking under sigmoid and Ji-Ji Earthquake (Sep. 21, 1999) excitation.
In another application, a neuro-fuzzy controller is developed for vibration suppression of building structures. A neuro-fuzzy system combines the advantages of neural network and fuzzy logic. Both neuro-fuzzy and neural classifier are implemented to the controller design of a building model. Experimental results show that both are effective to structure vibration suppression under free vibration, force vibration and Ji-Ji Earthquake (Sep. 21, 1999) excitation.

Agarwala, R., Ozcelik, S. and Faruqi, M., 2000, “Active Vibration Control of a Multi-Degree-of-Freedom Structure by the Use of Direct Model Reference Adaptive Control,” Proc. of the American Control Conf., Vol. 5, pp. 3580–3584.
Amini, F., Chen, H. M., Qi, G. Z. and Yang, J. C. S., 1997, “Generalized Neural Network Based Model for Structural Dynamic Identification, Analytical and Experimental Studies,” Proc. Intelligent Information Systems, pp. 138-142.
Baker, J. E., 1987, " Reducing Bias and Inefficiency in the Selection Algorithm," Proc. of the 2nd Int. Conf. on Genetic Algorithms and their Application, pp. 14-21.
Bani-Hani, K., Ghaboussi, J., and Schneider, S. P., 1999a, "Experimental Study of Identification and Control of Structures Using Neural Network. Part 1: Identification," Earthquake Engng. Struct. Dyn., vol. 28, no. 9, pp. 995-1018.
Bani-Hani, K., Ghaboussi, J., and Schneider, S. P., 1999b, "Experimental Study of Identification and Control of Structures Using Neural Network. Part 2: Control," Earthquake Engng. Struct. Dyn., vol. 28, no. 9, pp. 1019-1039.
Barada, S. and Singh, H., 1998, “Generating Optimal Adaptive Fuzzy-Neural Models of Dynamical Systems with Applications to Control,” IEEE Trans. on Syst., Man, and Cyber., Vol. 28, No. 3, pp. 371-391.
Billing, S. A. and Zheng, G. L., 1995, “Radial Basis Function Network Configuration Using Genetic Algorithms,” Neural Networks, vol. 8, no. 6, pp. 877-890.
Blickle, T. and Thiele, L., 1995, " A Comparison of Selection Schemes Used in Genetic Algorithms," TIK Report Nr. 11.
Booker, L., 1987, " Genetic Algorithms and Simulated Annealing," Morgan Kaufmann Publishers, pp. 61-73.
Castro, J. L., 1995, “Fuzzy Logical Controllers Are Universal Approximators,” IEEE Trans. Syst., Man, Cybern., Vol. 25, pp. 629-635.
Castro, J. L. and Delgado, M., 1996, “Fuzzy Systems with Defuzzification are Universal Approximators,” IEEE Trans. on Syst., Man, and Cyber., Vol. 26, No. 1, pp. 149-152.
Cavallo, A., De Maria, G. and Natale, C., 2001, “Second Order Sliding Manifold Approach for Vibration Reduction via Output Feedback: Experimental Results,” IEEE/ASME International Conf. on Advanced Intelligent Mechatronics Proc., Vol. 2, pp. 725–730.
Cerruto, E., Consoli, A., Raciti, A. and Testa, A., 1995, “A Robust Adaptive Controller for PM Motor Drives in Robotic Applications,” IEEE Trans. Power Electron., Vol. 10, pp. 62–71.
Chakraborty, D. and Pal, N. R., 2001, “Integrated Feature Analysis and Fuzzy Rule-Based System Identification in a Neuro-Fuzzy Paradigm,” IEEE Trans. Syst. Man Cybern. B, Vol. 31, pp. 391–400.
Chakraborty, D. and Pal, N. R., 2004, “A Neuro-Fuzzy Scheme for Simultaneous Feature Selection and Fuzzy Rule-Based Classification,” IEEE Trans. Neural Networks, Vol. 15, no. 1, pp. 110-123.
Chang, C. C., and Yu, L. O., 1998, "A Simple Optimal Pole Location Technique for Structural Control," Engineering Structures, vol. 20, no. 9, pp. 792-804.
Chang, H. C. and Wang, M. H., 1995, “Neural Network-Based Self-Organizing Fuzzy Controllers for Transient Stability of Multimachine Power Systems,” IEEE Trans. on Energy Conversion, Vol. 10, No. 2, pp. 339-347.
Chen, B. S., Chen, Y. Y. and Lin, C. L., 2003, “Nonlinear Guidance Against Maneuvering Target: Takagi-Sugeno fuzzy model Approach,” Intelligent Systems Techniques and Applications, Leondes, Ed. Boca Raton, FL: CRC to be published.
Chen, B. S. and Cheng, Y. M., 1998, “A Structure-Specified Optimal Control Design for Practical Applications: A Genetic Approach, 1998, ” IEEE Trans. Contr. Syst. Technol., Vol. 6, pp. 707–718.
Chen, C. I., Napolitano, M. R., and Smith, J. E., 1994, "Active Vibration Control Using the Modified Independent Modal Space Control (M.I.M.S.C.) Algorithm and Neural Networks as State Estimators," J. of Intell. Mater. Syst. and Struct., vol. 5, pp. 550-558.
Chen, H. M., Tsai, K. H., Qi, G. Z., Yang, J. C. S., and Amini, F., 1995, "Neural Network for Structure Control," J. of Computing in Civil Engineering, vol. 9, no. 2, pp. 168-176.
Chen, Y. C., and Teng, C. C., 1995, "Model Reference Control Structure Using a Fuzzy Neural Network," Fuzzy Sets and Systems, vol. 73, no. 3, pp. 291-312.
Chih, Y. H. and Kuo, Y. S., 1999, “A Novel Fuzzy Entropy Approach to Image Enhancement and Thresholding,” Signal Process. Vol. 75, pp. 277–301.
Damle, R., Rao, V., and Kern, F., 1997, "Robust Control of Smart Structures Using Neural Network Hardware," Smart Mater. Struct., vol. 6, no. 3, pp. 301-314.
Fadali, M., Zhang, Y. and Louis, S., 1999, “Robust Stability Analysis of Discrete-time Systems Using Genetic Algorithms,” IEEE Trans. Syst., Man, Cybern., Vol. 29, pp. 503-508.
Farag, W. A., Quintana, V. H. and Lambert-Torres, G., 1998, “A Genetic-based Neuro-fuzzy Approach for Modeling and Control of Dynamical Systems,” IEEE Trans. Neural Networks, Vol. 9, pp. 756-767.
Ferreira, R., Lopes, A. P. and Saraiva, T., 2000, “A Real Time Approach to Identify Actions to Prevent Voltage Collapse Using Genetic Algorithms and Neural Networks,” in Proc. IEEE Power Eng. Soc. Summer Meeting, Vol. 1, pp. 255-260.
Fogel, D. B., 1994, " An Introduction to Simulated Evolutionary Optimization," IEEE Trans. on neural networks, vol. 5, no. 1, pp. 3-14.
Fogel, L. J., Owens, A. J. and Walsh, M. J., 1966, " Artificial Intelligence through Simulated Evolution," New York: John Wiley.
Forrai, A., Hashimoto, S., Funato, H. and Kamiyama, K., 2001, “Structural Control Technology: System Identification and Control of Flexible Structures,” J. of Computing & Control Engineering, pp. 257-262.
Franco, B. Z., and Vilfrido, L. R., 1999, "Adaptive Control of Space Structures via Recurrent Neural Networks," Dynamics and Control, vol. 9, no. 1, pp. 5-20.
Fujita, S., Shibuya, M., Kawai, T., Shimoda, I., Mochimaru, M., Nagai, K., and Kimoto, K., 1997, "Impact Hybrid Mass Damper for High-Rise Buildings Against Destructive Earthquake Input," Trans. of JSME, vol. 63, no. 615, pp. 3840-3847.
Funahashi, K. I., 1989, “On the Approximate Relization of Continuous Mappings by Neural Networks,” Neural Networks, Vol. 2, pp. 183-192.
Geisler, J. P., Lee, C. S. G. and May, G. S., 2000, “Neurofuzzy Modeling of Chemical Vapor Deposition Process,” IEEE Trans. on Semiconductor Manufacturing, Vol. 13, No. 1, pp. 46-60.
Gen, M. and Cheng, R., 1997, “Genetic Algorithms and Engineering Design,” New York: Wiley.
Germano, L. T. and Carvalho, M. A., 2000, “Fitting Fuzzy Membership Functions Using Genetic Algorithms,” Syst. Man Cybern. Vol. 1, pp. 387 - 392.
Ghaboussi, J., and Joghataie, A., 1995, "Active Control of Structures Using Neural Networks," J. of Engineering Mechanics, vol. 121, no. 4, pp. 555-567.
Goldberg, D. E., 1989, “Genetic Algorithm in Search, Optimization, and Machine Learning Reading,” MA: Addison-Wesley.
Goode, P. V. and Chow, M. Y., 1995a, “Using a Neural/Fuzzy System to Extract Heuristic Knowledge of Incipient Faults in Induction Motors—Part I: Methodology, ”IEEE Trans. Ind. Electron., Vol. 42, pp. 131–138.
Goode, P. V. and Chow, M. Y., 1995b, “Using a Neural/Fuzzy System to Extract Heuristic Knowledge of Incipient Faults in Induction Motors—Part II: Application,” IEEE Trans. Ind. Electron., Vol. 42, pp. 139–146.
Grcar, B., Cafuta, P., Znidaric, M., and Gausch, F., 1996, “Nonlinear Control of Synchronous Servo Drive,” IEEE Trans. Contr. Syst. Technol., Vol. 4, pp. 177–184.
Haessig, D. A. and Friedland, B., 1991, “On the Modeling and Simulation of Friction,” Trans. ASME, J. Dyn. Syst., Meas., Control, Vol. 113, no. 5, pp. 354–362.
Hagras, H., Callaghan, V. and Colley, M., 2000, “Online Learning of Fuzzy Behavior Coordination for Autonomous Agents Using Genetic Algorithms and Real-time Interaction with the Environment,” Fuzzy Syst., Vol. 2, pp. 853 - 858.
Han, M., Han, G., Jiang, X. and Lian, Z., 2001, “Study of Dynamic Response of Dams with Neural Network,” IEEE International Conf. on Systems, Man, and Cybernetics, Vol. 1, pp. 134–139.
He, Y. A., and Wu, J., 1998, "Control of Structural Seismic Response by Self-Recurrent Neural Network (SRNN)," Earthquake Engng. Struct. Dyn., vol. 27, no. 7, pp. 641-648.
Hemati, N., Thorp, J. S. and Leu, M.C., 1990, “Robust Nonlinear Control of Brushless DC Motors for Direct-Drive Robotic Applications,” IEEE Trans. Ind. Electron., Vol. 37, pp. 460–468.
Hoare, T., Samali, B., and Kwok, K. C. S., 1994, "Control of Tall Buildings Using Acceleration Feedback Method Applied to Active Mass Dampers," Proc. of 2nd Int. Conf. on Motion and Vibration Control, pp. 132-137.
Holland, J. H., 1975, " Adaptation in Natural and Artificial Systems," Ann Arbor: The University of Michigan Press.
Horikawa, S., Furuhashi, T. and Uchikawa, Y., 1992, “On Fuzzy Modeling Using Fuzzy Neural Networks with the Back-Propagation Algorithm,” IEEE Trans. on Neural Networks, Vol. 3, No. 5, pp. 801-806.
Hsu, C., Tse, K. and Wang, C., 1997, “Digital Redesign of Continuous Systems with Improved Suitability Using Genetic Algorithms,” Electron. Lett., Vol. 33, no. 15, pp. 1345-1347.
Huang, Y. P. and Yu, T. M., 1997, “The Hybrid Grey-based Models for Temperature Prediction,” IEEE Trans. Syst., Man, Cybern. B, Vol. 27, pp. 284–292.
Hung, S. L. and Adeli, H., 1994, “A Parallel Genetic/Neural Network Learning Algorithm for MIMD Shared Memory Machines,” IEEE Trans. Neural Networks, vol. 5, no. 6, pp. 900-909.
Ioannou, P. A., and Sun, J., 1996, “Robust Adaptive Control,” Englewood Cliffs, NJ: Prentice-Hall.
Ishibuchi, H., Fujioka, R. and Tanaka, H., 1993, “Neural Networks That Learn from Fuzzy If-Then Rules,” IEEE Trans. on Fuzzy Syst., Vol. 1, No. 2, pp. 85-97.
Itoh, K., Iwasaki, M. and Matsui, N., 2004, “Optimal Design of Robust Vibration Suppression Controller Using Genetic Algorithms,” IEEE Trans. Ind. Electron., Vol. 51, no. 5, pp. 947–953.
Jabbari, F., Schmitendorf, W. E., and Yang, J. N., 1995, “ Control for Seismic-Excited Building with Acceleration Feedback,” J. of Engineering Mechanics, vol. 121, no. 9, pp. 994-1002.
Jacobs, R. A., 1988, “Increased Rates of Convergence Through Learning Rate Adaptation,” Neural Networks, Vol. 1, pp. 295-307.
Jagannathan, S., 2001, “Control of a Class of Nonlinear Discrete-Time Systems Using Multilayer Neural Networks,” IEEE Trans. Neural Networks, Vol. 12, no. 5, pp. 1113-1120.
Jang, J. S., 1992, “Self-Learning Fuzzy Controllers Based on the Temporal Back Propagation,” IEEE Trans. on Neural Networks, Vol. 3, No. 5, pp. 714-723.
Jang, J. S. and Sun, C. T., 1995, “Neuro-Fuzzy Modeling and Control,” Proc. of the IEEE, Vol. 83, No. 3, pp. 378-406.
Jeng, C. A., Yang, S. M. and Lin, J. N., 1997, “Multi-Mode Control of Structures by Using Neural Networks with Marquardt Algorithms,” Journal of Intelligent Material Systems and Structures, Vol. 8, no. 12, pp. 1035-1043.
Jin, Y., Jiang, J. and Zhu, J., “Neural Network Based Fuzzy Identification and Its Application to Modeling and Control of Complex Systems,” IEEE Trans. on Syst., Man, and Cyber., Vol. 25, No. 6, pp. 990-997, 1995.
Johnson, G. T. and Lorenz, R. D., 1992, “Experimental Identification of Friction and It’s Compensation in Precise, Position Controlled Mechanisms,” IEEE Trans. Ind. Applicat., Vol. 28, pp. 1392–1398.
Kasabov, N. and Song, Q., 2002, “DENFIS: Dynamic Evolving Neural-Fuzzy Inference System and Its Application for Time Series Prediction,” IEEE Trans. Fuzzy Syst..
Kazuto, S., 1996, “A Structural Method of the Vibration Control of Flexible Buildings in Response to Large Earthquakes and Strong Winds,” Proc. 1st Int. Conf. Motion and Vibration Control, pp. 658–663.
Kempf, C. J., and Kobayashi, S., 1999, “Disturbance Observer and Feedforward Design for a High-Speed Direct-Drive Positioning Table,” IEEE Trans. Control Syst. Technol., Vol. 7, pp. 513–526.
Kim, J. H., Jabbari, F. and Yang, J. N., 2000, “Actuator Saturation and Control Design for Buildings Under Seismic Excitation,” Proc. of the American Control Conf., Vol. 1, PP. 29–33.
Kohonen, T., 1988, “Self-Organization and Associative Memory,” Berlin: Springer- Verlag.
Kosko, B., 1992, “Fuzzy System as Universal Approximators,” IEEE Int. Conf. Fuzzy Syst., pp.1153-1162.
Kristinsson, K. and Dumont, G., 1999, “System Identification and Control Using Genetic Algorithms,” IEEE Trans. Syst., Man, Cybern., Vol. 22, pp. 1033-1046.
Ku, C. C. and Lee, K. Y., 1995, “Diagonal Recurrent Neural Networks for Dynamic Systems Control,” IEEE Trans. Neural Networks, Vol. 6, no. 1, pp. 144-155.
Kundu, S., Seto, K. and Sugino, S., 2002, “Genetic Algorithm Application to Vibration Control of Tall Flexible Structures,” IEEE Proc., Electr. Design, Test and Appl., pp. 333–337.
Lee, H. S., and Tomizuka, M., 1996, “Robust Motion Controller Design for High-Accuracy Positioning Systems,” IEEE Trans. Ind. Electron., Vol. 43, pp. 48–55.
Lee, T. S., Chen, Y. H. and Chuang, C. H., 1997, “Robust Control of Building Structures,” Proc. of the American Control Conf., Vol. 5, PP. 3421–3425.
Leu, Y. G., Wang, W. Y. and Lee, T. T., 1999, “Robust Adaptive Fuzzy-neural Controllers for Uncertain Nonlinear Systems,” IEEE Trans. Robotics Automat., Vol. 15, pp. 805-817.
Levin, A. U. and Narendra, K. S., 1996, “Control of Nonlinear Dynamical Systems Using Neural Networks—Part II: Observability, Identification, and Control,” IEEE Trans. Neural Networks, Vol. 7, pp. 30–42.
Li, C., and Liu, Y., 1999, "Tuned Mass Damper Control Optimum Design of Tall Buildings Under Earthquake," J. of Tongji University, vol. 27, no. 3, pp. 287-291.
Li, H., Mao, C. X., Ou, J. P. and Li, Z. W., 2003, “Advanced Health Monitoring and Damage Repair Technologies by Using Shape Memory Alloys,” Proceedings of Smart Materials and Structures, Stanford, USA.
Li, H., Yuan, X. S. and Wu, B., 2002, “Variable Orifice Dampers: Experiments and Analysis,” Journal of Engineering Vibration, Vol. 15, pp. 25-30.
Li, Y., and Tomizuka, M., 1999, “Two-degree-of-freedom Control with Robust Feedback Control Hard Disk Servo Systems,” IEEE Trans. Mechatronics, 1999, Vol. 4, pp. 17–24.
Liaw, C. M., Shue, R. Y., Chen, H. C., and Chen, S. C., 2001, “Development of a Linear Brushless DC Motor Drive with Robust Position Control,” IEE Proc., Electr. Power Appl., Vol. 148, pp. 111–118.
Lin, C. L., Jan, H. Y. and Shieh N. C., 2003, “GA-Based Multiobjective PID Control for a Linear Brushless DC Motor,” IEEE Trans. on Mech., Vol. 8, no. 1, pp. 56-65.
Lin, C. T., 1994, “Neural Fuzzy Control Systems with Structure and Parameter Learning”, World Scientific.
Lin, C. T., 1995, “A Neural Fuzzy Control System with Structure and Parameter Learning,” Fuzzy Sets Syst., Vol. 70, Issue 2-3, pp. 183-212.
Lin, C. T. and Jou, C. P., 2000, “GA-based Fuzzy Reinforcement Learning for Control of a Magnetic Bearing System,” IEEE Trans. Syst., Man, Cybern. B, Vol. 30, pp. 276-289.
Lin, C. T., Juang, C. F. and Li, C. P., 1999, “Temperature Control with a Neural Fuzzy Inference Network,” IEEE Trans. on Syst., Man, and Cyber., Vol. 29 No. 3, pp. 440-451.
Lin, C. T. and Lee, C. S. G., 1991, “Neural-Network-Based Fuzzy Logic Control and Decision System,” IEEE Trans. on Computers., Vol. 40, No. 12, pp. 1320-1336.
Lin, C. T., and Lu, Y. C., 1996, “A Neural Fuzzy System with Fuzzy Supervised Learning,” IEEE Trans. on Syst., Man, and Cyber., Vol. 26, No. 5, pp. 744-763.
Lin, F. J., Shyu, K. K. and Lin, Y. S., 1999, “Variable Structure Adaptive Control for PM Synchronous Servo Motor Drive,” IEE Proc. IEE B: Elect. Power Applicat., Vol. 146, pp. 173–185.
Lin, L. C. and Lin, T. Y., 2001, “An Design Approach for Neural Net-Based Control Schemes,” IEEE Trans. Automat. Contr., Vol. 46, pp. 1599–1605.
Liu, Z. Z., Luo, F. L., Rashid, M. H., 2004, “Robust High Speed and High Precision Linear Motor Direct-Drive XY-table Motion System,” IEEE Proc.-Control Theory Appl., Vol. 151, No. 2, pp. 166-173.
Liut, D. A., Matheu, E. E., Singh, M. P., and Mook, D. T., 1999, "Neural-Network Control of Building Structures by a Force-Matching Training Scheme," Earthquake Engng. Struct. Dyn., vol. 28, no. 12, pp. 1601-1620.
Lu, Q., Peng, Z., Chu, F. and Huang, J., 2003, “Design of Fuzzy Controller for Smart Structures Using Genetic Algorithms,” Institute of Physics Publishing. Vol. 12, pp. 979–986.
Luciano, A. M. and Savastano, M., 1997, “Fuzzy Identification of Systems with Unsupervised Learning,” IEEE Trans. Syst., Man, Cybern. B, Vol. 27, pp. 138-141.
Makris, N., 1997, “Vibration Control of Structures During Urban Earthquakes,” Proc. of the American Control Conf., Vol. 6, pp. 3957-3961.
Maniezzo, V., 1994, “Genetic Evolution of the Topolgy and Weight Distribution of Neural Networks,” IEEE Trans. Neural Networks, vol. 5, no. 1, pp. 39-53.
Marino, R., Peresada, S., and Valigi, P., 1993, “Adaptive Input–Output Linearizing Control of Induction Motors,” IEEE Trans. Automat. Contr., Vol. 38, pp. 208–221.
Michalewicz, Z., 1996, “Genetic Algorithms + Data Structures = Evolution Programs,” New York: Springer-Verlag.
Michalewicz , Z. and Krawezyk, J. B., 1992, “A Modified Genetic Algorithm for Optimal Control Problems,” Comput. Math. Appl., Vol. 23, pp. 83–94.
Minai, A. A., and Williams, R. D., 1990, "Acceleration of Backpropagation Through Learning Rate and Momentum Adaptation," IJCNN, Vol. I, pp. 676-679.
Minato, J. and Ohsumi, A., 2003, “Control for High-rise Buildings Subjected to Wind and Seismic Disturbances,” SICE 2003 Annual Conference, Vol. 1, pp. 535–539.
Mita, A., and Kaneko, M., 1992, "Hybrid Verse Tuned or Active Mass Dampers for Response Control of Tall Buildings," Proc. of 1st Int. Conf. on Motion and Vibration Control, pp. 304-309.
Mitra, S., and Hayashi, R., 2000, “Neuro-Fuzzy Rule Generation: Survey in Soft Computing Framework,” IEEE Trans. on Neural Networks, Vol. 11, No. 3, pp. 748-768.
Mitra, S., and Pal, S. K., 1996, “Fuzzy Self-Organization, Inferencing, and Rule Generation,” IEEE Trans. on Syst., Man, and Cyber., Vol. 26, No. 5, pp. 608-620.
Narendra, K. S. and Parthasarathy, K., 1990, “Identification and Control of Dynamical Systems Using Neural Networks,” IEEE Trans. Neural Networks, Vol. 1, no. 1, pp. 4-27.
Nauck, D. and Kruse, R., 1993, “A Fuzzy Neural Network Learning Control Rules and Membership Functions by Fuzzy Error Backpropagation,” Proc. IEEE Int. Conf. Neural Networks, pp. 1022-1027.
Ng, K. C. and Trivedi, M. M., 1998, “A Neuro-Fuzzy Controller for Mobile Robot Navigation and Multirobot Convoying,” IEEE Trans. on Syst., Man, and Cyber., Vol. 28 No. 6, pp. 829-840.
Nguyen, T., Jabbari, F. and Miguei, S. D., 1998, “Application of Active Control to Buildings Under Seismic Excitation: Actuator Saturation,” Proc. of the 1998 IEEE International Conf. on Control Appl., Vol. 2, pp. 1051-1055.
Nishimura, H. and Kojima, A., 1999, “Seismic Isolation Control for a Building-Like Structure,” IEEE Control Systems Magazine, pp. 38-44.
Nishimura, I., Kobori, T., Sakamoto, M., Koshika, N., Sasaki, K., and Ohrui, S., 1992, "Acceleration Feedback Method Applied to Active Tuned Mass Damper," Proc. of 1st Int. Conf. on Motion and Vibration Control, pp. 273-278.
Nishitani, A., Nitta, Y. and Yamada, N., 1996, “Variable Gain-Based Structural Control Considering the Limit of AMD Movement,” Proc. of the 35th IEEE Conf. on Decision and Control, Vol. 1, pp. 185–190.
Nomura, H., Hayashi, I. and Wakami, N., 1992, “A Learning Method of Fuzzy Inference Rules by Descent Method,” in Proc. IEEE Int. Conf. Fuzzy Syst., Mar. pp. 203-210.
Ohnishi, K., Shibata, M., and Murakami, T., 1996, “Motion Control for Advanced Mechatronics,” IEEE/ASME Trans. Mechatronics, Vol. 1, pp. 56–67.
Ohnishi, K., Ueda, Y. and Miyachi, K., 1986, “Model Reference Adaptive System Against Rotor Resistance Variation in Induction Motor Drive,” IEEE Trans. Ind. Electron., Vol. 4, pp. 217–223.
Omatu, S., Khalid, M. and Yusof, R., 1997, “Neuro-Control and Its Applications,” Berlin, Germany: Springer-Verlag.
Ou, J. P., 2002, “Active Mass Damper with Magnetic-Suspension Driver,” Patent of China.
Ou, J. P., 2003, “ Structural Vibration Control-Active, Semi-Active and Smart Control Systems,” Press of Science, China.
Ou, J. P. and Li, H., 2004, “Active Control Force Characteristics and Design Approaches of Semi-active Control Systems,” Proc. of the SE04, Osaka, Japan.
Oya, M., Su, C. Y. and Katoh, R., 2003, “Robust Adaptive Motion/Force Tracking Control of Uncertain Nonholonomic Mechanical Systems,” IEEE Transactions on Robotics and Automation, Vol. 19, pp. 175-181.
Ozaki, T., 1991, “Trajectory Control of Robotic Manipulators Using Neural Network,” IEEE Trans. Ind. Electron., Vol. 38, pp. 195–202.
Pal, K., Mudi, R. and Pal, N. R., 2002, “A New Scheme for Fuzzy Rule Based System Identification and Its Application to Self-Tuning Fuzzy Controllers,” IEEE Trans. Syst. Man Cybern. B, Vol. 32, pp. 470–482.
Pal, N. R. and Pal, T., 1999, “On Rule Pruning Using Fuzzy Neural Networks,” Fuzzy Sets Syst., Vol. 106 Issue 3, pp. 335-347.
Pal, S. K. and Mitra, S., 1992, “Multilayer Percepotron, Fuzzy Sets, and Classification,” IEEE Trans. on Neural Networks, Vol. 3, No. 5, pp. 683-697.
Paul, S. and Kumar, S., 2002, “Subsethood-Product Fuzzy Neural Inference System,” IEEE Trans. Neural Networks, vol. 13, pp. 578–599.
Pelczewski, P. M. and Kunz, U. H., 1990, “The Optimal Control of a Constrained Drive System with Brushless DC Motor,” IEEE Trans. Ind. Electron., Vol. 37, pp. 342–348.
Popescu, T. D., 2001, “Robust Change Detection Method with Application in Vibration Structures Monitoring,” Proc. of 8th IEEE International Conf. on Emerging Technologies and Factory Automation, Vol. 1, pp. 95-102.
Prasanna, B. and Mutsuo, N., 1999, “A Servo System Tracking Controller Based on Neural Networks,” IEEE Contr. Power Electronics and Drive System, pp. 809–814.
Psaltis, D., Sideris, A. and Yamamura, A., 1988, “A Multilayer Neural Network Controller,” IEEE Contr. Syst. Mag., pp. 17–21.
Qiao, H., Peng, J. and Xu, Z. B., 2003, “A Reference Model Approach to Stability Analysis of Neural Networks,” IEEE Transactions on Systems Man and Cybernetics, Part B, Vol. 33, No. 6, pp. 925-936.
Rechenberg, I., 1973, " Evolutionsstrategie - Optimierung Technischer Systeme Nach Prinzipien der Biologischen Evolution," Stuttgart: Frommann-Holzboog.
Rubaai, A., 2003, “Implementation of an Intelligent-Position-Controller-Based Matrix Formulation Using Adaptive Self-Tuning Tracking Control,” IEEE Trans. on Ind. Appli., Vol. 39, no. 3, pp. 627–636.
Rumelhart, D. E., Hinton, G. E., and Williams, P. J., 1986, "Learning Internal Representation by Error Propagation," in Parallel Distributed Processing, Eds. Cambridge, MA: MIT Press.
Sastry, P. S., Santharam, G. and Unnikrishnan, K. P., 1994, “Memory Neuron Networks for Identification and Control of Dynamical Systems,” IEEE Trans. Neural Networks, Vol. 5, pp. 306–319.
Sastry, S. S. and Bodson, M., 1989, “Adaptive Control: Stability, Convergence, and Robustness,” Englewood Cliffs, NJ: Prentice-Hall.
Schwefel, H. P., 1981, " Genetic Algorithms and Simulated Annealing," Chichester: Wiley & Sons.
Seto, F. and Matsumoto, Y., 1999, “Active Vibration Control of Multiple Buildings Connected with Active Control Bridges in Response to Large Earthquakes,” Proc. of the American Control Conf., Vol. 2, PP. 1007–1011.
Seto, K., 1992, "Trends on Active Vibration Control," Proc. of 1st Int. Conf. on Motion and Vibration Control, vol. 1, pp. 1-11.
Shann, J. J. and Fu, H. C., “A Fuzzy Neural Network for Rule Acquiring on Fuzzy Control System,” Fuzzy Sets Syst., Vol. 71, Issue 3, pp. 345-357, 1995.
Shieh, N. C., and Tung, P. C., 2001, “Robust Output Tracking Control of a Linear DC Brushless Motor for Transportation in Manufacturing System,” IEEE Proc., Electr. Power Appl., Vol. 148, pp. 119–124.
Sin, J. K. and Jae, W. C., 2000, “Parametric Uncertainty in Controlling the Vibration of a Building,” Proceedings of the 39th SICE Annual Conference, pp. 107 - 112.
Soong, T. T., 1988, "Active Structural Control in Civil Engineering," Engineering Structure, vol. 10, pp. 78-84.
Spears, W. M. and De Jong, K. A., 1991, " An Analysis of Multi-Point Crossover," Morgan Kaufmann Publishers, pp. 301-315.
Sridhar, S. and Hassan, K. K., 2000, “Output Feedback Control of Nonlinear Systems Using RBF Neural Networks,” IEEE Trans. Neural Networks, Vol. 11, no. 1, pp. 69-79.
Su, M. C., Liu, C. W. and Tsay, S. S., 1999, ”Neural-Network-Based Fuzzy Model and Its Application to Transient Stability Prediction in Power Systems,” IEEE Trans. on Syst., Man, and Cyber., Vol. 29, No. 1, pp. 149-157.
Sugeno, M. and Yasukawa, T., 1993, “A Fuzzy-Logic-Based Approach to Qualitative Modeling,” IEEE Trans. on Fuzzy Syst., Vol. 1, No. 1, pp. 7-31.
Sundareshan, M. K., and Askew, C., 1997, "Neural Network-Assisted Variable Structure Control Scheme for Control of a Flexible Manipulator Arm," Automatica, vol. 33, no. 9, pp. 1699-1710.
Suzuki, Y., 1998, “Acceleration Feedforward Control for Active Magnetic Bearing Systems Excited by Ground Motion,” Proc. Control Theory Appl., Vol. 145, pp. 113–118.
Tai, H. M., 1992, “Trajectory Tracking Using Neural Network,” IEEE Trans. Contr. Syst. Technol., Vol. 6, pp. 2929–2932.
Tanaka, H., Ishibuchi, H. and Fujioka, R., “Neural Networks That Learn from Fuzzy If-Then Rules,” IEEE Trans. on Fuzzy Syst., Vol. 1, No. 2, pp. 85-97, 1993.
Tani, A. and Kawamura, H., 1993, “Fuzzy Optimal Seismic Control Systems of Buildings-In Case of Active Equivalent Variable Mass System,” Proc. of Second International Symposium on Uncertainty Modeling and Analysis, pp. 611-618.
Tsakalis, K. S. and Ioannou, P. A., 1993, “Linear Time-Varying Systems,” Englewood Cliffs, NJ: Prentice-Hall.
Tseng, H. C. and Hwang, V. H., 1993, “Servo Controller Tuning with Fuzzy Logic,” IEEE Trans. Contr. Syst. Technol., Vol. 1, pp. 262–269.
Tzou, Y. Y., 1996, “DSP-based Robust Control of an AC Induction Servo Drive for Motion Control,” IEEE Trans. Contr. Syst. Technol., Vol. 4, pp. 614–626.
Umeno, T., and Hori, Y., 1991, “Robust Speed Control of DC Servomotors Using Modern Two Degree-of-Freedom Controller Design,” IEEE Trans. Ind. Electron., Vol. 38, pp. 363–368.
Utkin, V. I., 1993, “Sliding Mode Control Design Principles and Applications to Electric Drives,” IEEE Trans. Ind. Electron., Vol. 40, pp. 23–36.
Vlachos, C., Williams, D. and Gomm, J. B., 1999, “Genetic Approach to Decentralized PI controller Tuning for Multivariable Processes,” IEE Proc. Control Theory Applicat., Vol. 146, pp. 58–64.
Vogl, T. P., Mangis, J. K., Rigler, A. K., Zink, W. T., and Alkon, D. L., 1988, "Accelerating the Convergence of the Backpropagation Method," Biological Cybernetics, Vol. 59, pp. 257-263.
Wai, R. J., 2003, “Development of Intelligent Position Control System Using Optimal Design Technique,” IEEE Trans. on Ind. Electron., Vol. 50, no. 1, pp. 218–231.
Wai, R. J. and Chen, P. C., 2004, “Intelligent Tracking Control for Robot Manipulator Including Actuator Dynamics via TSK-Type Fuzzy Neural Network,” IEEE Trans. on Fuzzy. Syst., Vol. 12, no. 4, pp. 552–559.
Wang, C. H. and Hong, T. P., 2000, “Integrating Membership Functions and Fuzzy Rule Sets from Multiple Knowledge Sources,” Fuzzy Sets Syst. Vol. 112, pp. 141 - 154.
Wang, C. H., Liu, H. L. and Lin, C. T., 2001, “Dynamic Optimal Learning Rates of a Certain Class of Fuzzy-neural Networks and Its Applications with Genetic Algorithm,” IEEE Trans. Syst., Man, Cybern. B, Vol. 31, pp. 467-475.
Wang, C. H., Wang, W. Y., Lee, T. T. and Tseng, P. S., 1995, “Fuzzy B-Spline Membership Function (BMF) and its Applications in Fuzzy-Neural Control,” IEEE Trans. Syst., Man, Cybern., Vol. 25, pp. 841-851.
Wang, G. J., Fong, C. T. and Chang, K. J., 2001, “Neural-Network-Based Self -Tuning PI Controller for Precise Motion Control of PMAC Motors,” IEEE Trans. on Ind. Electron., Vol. 48, no. 2, pp. 408–415.
Wang, L. and Langari, R., 1996, “Complex Systems Modeling via Fuzzy Logic,” IEEE Trans. on Syst., Man, and Cyber., Vol. 26, No. 1, pp. 100-106.
Wang, L. X., 1994, “Adaptive Fuzzy Systems and Control,” Englewood Cliffs, NJ: Prentice-Hall.
Wang, W. Y., Chan, M. L., Hsu, C. C. and Lee, T. T., 2002, “Tracking-Based Sliding Mode Control for Uncertain Nonlinear Systems via an Adaptive Fuzzy-Neural Approach,” IEEE Trans. Syst., Man, Cybern. B, Vol. 32, pp. 483-492.
Wang, W. Y., Cheng, C. Y. and Leu, Y. G., 2004, “An Online GA-Based Output -Feedback Direct Adaptive Fuzzy-Neural Controller for Uncertain Nonlinear Systems,” IEEE Trans. Syst., Man, Cybern. B, Vol. 34, no. 1, pp. 334-345.
Wit, C. D., Olsson, H., Astrom, K. J., and Lischinsky, P, 1995, “A New Model for Control of Systems with Friction,” IEEE Trans. Automat. Contr., Vol. 40, pp. 419–425.
Wong, S. V. and Hamouda, A. M. S., 1999, “Optimization of Fuzzy Rules Design Using Genetic Algorithm,” Advances in Engineering Software, Vol. 31, pp. 251–262.
Yamada, N., Watanabe, M., and Nishitani, A., 1994, " Control Design of Buildings with System Identification Technique," Proc. of 2nd Int. Conf. on Motion and Vibration Control, pp. 114-119.
Yamaguchi, T., Soyama, Y., and Hosokawa, H., 1996, “Improvement of Settling Response of Disk Drive Head Positioning Servo Using Mode Switching Control with Initial Value Compensation,” IEEE Trans. Magn., Vol. 32, pp. 1767–1772.
Yamamoto, K., Yamamoto, T., Ohmori, H. and Sano, A., 1997, “Adaptive Feedforward Control Algorithms for Active Vibration Control of Tall Structures,” Proc. of the 1997 IEEE International Conf. on Control Appl., pp. 736 – 742.
Yang, S. M. and Huang, W. L., 2002, “System Identification and Control by Using Feedforward Network with Two-Stage Training Algorithm,” CSSV Conf. Taiwan, pp. 274-280.
Yang, S. M., and Lee, G. S., 1997a, "Vibration Control of Smart Structures by Using Neural Networks," J. of Dynamic Systems, Measurement, and Control, ASME, vol. 119, no. 1, pp. 34-39.
Yang, S. M., and Lee, G. S., 1997b, "A Neural Network Design Methodology for Structural Control," 1997 ASME Design Engineering Technical Conferences, Paper No.: DETC97/VIB-3775.
Yang, S. M., and Lee, G. S., 1997c, "System Identification of Smart Structures Using Neural Networks, " J. of Intell. Mater. Syst. and Struct., vol. 8, no. 10, pp. 883-890.
Yang, S. M. and Tung, Y. J., 2001, “A Neuro-Fuzzy System Design Methodology for Modeling and Control,” 4th Pacific International Conference on Aerospace Science and Technology, Kaohsing, Taiwan.
Yang, S. M., Tung, Y. J. and Huang, W. L., 2002, “A Neuro-Fuzzy System and Its Applications to Modeling and Control,” CSSV Conf. Taiwan, pp. 35-42.
Yang, Y. P., 1993, “Adaptive Velocity Control of DC Motor with Coulomb Friction Identification,” Trans. ASME, J. Dyn. Syst., Meas., Control, Vol. 115, no. 2, pp. 95–102.
Yi, F., Dyke, S. J., Caicedo, J. M. and Carlson, J. D., 1999, “Seismic Response Control Using Smart Dampers,” Proc. of the American Control Conf., Vol. 2, pp. 1022–1026.
Yoshida, K., 1994, "Frontiers of Active Motion and Vibration Control," Proc. of 2nd Int. Conf. on Motion and Vibration Control, pp. 1-10.
Yu, W. and Li, X., 2001, “ Some New Results on System Identification with Dynamic Neural Networks,” IEEE Trans. Neural Networks, Vol. 12, no. 2, pp. 412-417.
Yu, X. H. and Chen, G. A., 1997, “Efficient Backpropagation Learning Using Optimal Learning Rate and Momentum,” Neural Networks, Vol. 10, no. 3, pp. 517-527.
Yu, X. H., Chen, G. A. and Cheng, S. X., 1995, “Dynamic Learning Rate Optimization of the Backpropagation Algorithm,” IEEE Trans. Neural Networks, Vol. 6, no. 3, pp. 669-677.
Zhang, J. and Morris, A. J., 1995, “Fuzzy Neural Network for Nonlinear Systems Modeling,” IEEE Proc. Control Theory Appl., Vol. 142, No. 6, pp. 551-561.
Zhang, Y. Q. and Kandel, A., “Compensatory Neurofuzzy Systems with Fast Learning Algorithms,” IEEE Trans. on Neural Networks, Vol. 9, No. 1, pp. 83-105, 1998.
Zhong, H. Y., Behera, A. K. and Rashid, M. H., 1991, “8096 Microcontroller Based Field Acceleration Method Control for Induction Motor with New Digital PWM Inverter Technique,” in Conf. Rec. IEEE-IAS Annu. Meeting, pp. 1662–1668.
Zhou, K., Doyle, J. C. and Glover, K., 1996, “Robust and Optimal Control,” NJ: Prentice-Hall.