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Title page for etd-0213107-172847


URN etd-0213107-172847 Statistics This thesis had been viewed 3146 times. Download 1125 times.
Author Jui-Chi Chang
Author's Email Address No Public.
Department Electrical Engineering
Year 2006 Semester 2
Degree Ph.D. Type of Document Doctoral Dissertation
Language Chinese&English Page Count 102
Title CMAC-BASED PID AND SMC CONTROLLER DESIGN
Keyword
  • CMAC
  • PID
  • SMC
  • SMC
  • PID
  • CMAC
  • Abstract Applying the cerebellar mode articulation controller (CMAC) to the PID and SMC controllers is presented in this dissertation. The CMAC can be thought as a framework that imitates the stored property of information about cerebellum of human being. In this structure, the continuous input and output space are quantified some discrete input and output patterns. As cerebellum of human being enhances the faculty of memory by the policy of learning, CMAC has fine completed ability via iterative learning of these trained patterns. The association cell index of CMAC activated by the input vector addresses memories to determine the output. The properties of CMAC are as follows: a kind of lookup table method, faster convergence, good function approximation, and generalization ability.
    A new direct-action CMAC PID (DAC-PID) controller is proposed. This proposed controller uses the function approximation and generalization ability of CMAC to learn the proposed nonlinear function. All parameters of the controller and of the nonlinear function are optimization by using the genetic algorithm. A CMAC directly is used to output proportional-type control effort after completely learn this optimum nonlinear function. The P-type, I-type, and D-type control effort is generated by PID structure, respectively. The proposed controller can enhance the conventional PID controller by using the nonlinear control effort. The simulation shows the proposed controller has satisfactory results.
    A hybrid adaptive CMAC sliding mode control system (HAC-SMC) is developed for a class of unknown nonlinear system. Sliding control effort is the sum of the equivalent control effort and the switching control effort. The equivalent control effort needs the information of nonlinear function. However, in practice, these nonlinear functions can not be known exactly. CMAC has function approximation and generalization ability. Hence, CMAC is used to approximate these unknown nonlinear functions. The hybrid adaptive CMAC to perform the equivalent control effort of the sliding mode control by using the indirect adaptive CMAC controller and direct adaptive CMAC controller. A weight factor is adopted to sum these control efforts from direct CMAC controller and indirect controller. A switching controller is adopted by a sign function and has an adaptive law to estimate the upper bound. Besides, a CMAC switching controller is proposed to emulate the switching control effort. Next, a supervisory controller is appended to the hybrid adaptive CMAC sliding mode controller to guarantee the states can stay in the boundary layer. If the hybrid adaptive controller can maintain the states in the boundary layer, this supervisory controller disables, and vice versa. Furthermore, the adaptive laws of the control system are derived by the Lyapunov theorem. Hence, the stability of the system is guaranteed. Finally, the simulation shows the proposed controller has satisfactory performance.
    Advisor Committee
  • Hung-Ching Lu - advisor
  • Ching-Chang Wong - co-chair
  • none - co-chair
  • none - co-chair
  • none - co-chair
  • none - co-chair
  • Files indicate in-campus access at 2 years and off-campus access at 3 years
    Date of Defense 2007-01-31 Date of Submission 2007-02-14


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