Real time self-tuning of industrial controllers using a digital parameter optimization technique

A digital, parametrically optimized adaptive self-tuning regulator is proposed for the on-line tuning of motor controllers. The proposed adaptive technique consists of an identification scheme which identifies the system with a predictive model and a parameter optimization control technique which uses this model to derive the control law. The control design consists of choosing a suitable regulator structure, then tuning the associated regulator parameters to minimize a chosen minimization criterion. The proposed design technique has flexibility in specifying the order and structure of the regulator which offers advantages in selecting and autotuning well known effective controller structures. The computations involved in the proposed controller are feasible for implementation by an on-line microprocessor. Examples are presented which show that the proposed technique outperforms the fixed parameters controllers by a great deal