Self Adaptive Control

Basically self-adaptive control is one of the major types of the adaptive control. And it is comparable to the feedback compensation because the adaptation of controller parameters is based on the closed-loop performance measurement and the objective is to optimize it using process reference models or estimation techniques. In self-adaptive control, the controller parameters are generated for each process condition and are the not programmed as in the case of programmed adaptive control. The parameter adjustment loop searches for optimal values for the controller parameters on-line.

Types of Self Adaptive Control

Model Reference Adaptive Control (MRAC).
Self Tuning Regulator (STR).

Model Reference Adaptive Control

Model Reference Adaptive Control is also known as the MRAC. Basically process parameters are unknown or vary with time, an adaptive control scheme known as the model reference adaptive control (MRAC) is applied to achieve as well as maintain the desired performance. Here, a reference model is the realization of a process with the desired performance. This scheme is based on the observation that the output of the process and the output of the reference model ( is also called the process-model error) is a measure of the difference between actual and desired performance. And adjustment mechanism directly adjusts the parameters of the controller to bring the process-model error to zero in real time. MRAC is also known as the direct adaptive control due to the direct adjustment of controller parameters using the model output.

Self Tuning Regulator

Self Tuning Regulator is also known as the STR. The basic idea of Self Tuning Regulator is that a suitable controller can be designed online if the process parameters are estimated on line from available input output measurements. This process output and the forecasted or predicted output are compared. And the adaptation mechanism uses the error between the process output and the predicted output ( is also called the prediction error or process-model error) to adjust the controller parameters to minimize the prediction error under specified conditions. Self Tuning Regulator is also known as indirect adaptive control because the adaptation of controller parameters is done through on line estimation of the process parameters.