Table of contents iv List of figures vi List of tables Principal symbols xi 10 2.2 The Heffron-Phillips Model for a Single-Machine Plant 2.3 Generalized Heffron-Phillips Model for a Multimachine Plant 18 2.4 Including the AVR's in the Generalized Heffron-Phillips Model 28 2.5 The Data of a Three Machine Plant and Its Model 31 3. OPTIMAL CONTROLLER DESIGN 38 3.
PID neural network (PIDNN) controller was designed, and the adaptive mutation particle swarm optimization (PSO) algorithm is adopted to train and update its weights. The adaptive mutation PSO-PIDNN learning algorithm of motor synchronization control was put forward. According to the need of engineering, the algorithm was simplified. In proportion of multiple motor synchronization control system simulation show that the simplified PSO-PIDNN controller also can effectively realize the motor synchronization control, solve the problem of the parameter setting is not easy for traditional PID control, has good stability and fast convergence speed, no overshoot. □□□□□□□□□□□
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