Auto-Tuning by Using Double Extended Kalman-Bucy Filter: An Application to Dc Motor for Controlling Speed

Auto-Tuning by Using Double Extended Kalman-Bucy Filter: An Application to Dc Motor for Controlling Speed

In this study, a modified adaptive control algorithm is proposed and investigated. The algorithm consists of a controller, an estimator and an auxiliary model like in model reference adaptive control strategy. PID controller is used to provide controlling. The controller includes adjustable parameters. Traditional PID controller parameters are usually set to fulfil the reference behaviour criterion. In this study, minimum-time criterion is chosen. Extended Kalman-Bucy estimator is employed for estimating controller parameters to make system behave like auxiliary model. The estimator adjusts the controller parameters so that system output can catch the reference input at minimum time. The study may call as the minimization of the settling time problem. The controller and estimator of the system are operated simultaneously. The achievement of the proposed algorithm is proved by simulation results including a simple dc motor model.

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