Adaptive control refers to a control method that is used by a controller that must adapt to a controlled system with varying or uncertain parameters. Adaptive control detects the changes in the functioning of the process and regulates the controlling parameters automatically to compensate for the altering conditions of the process and, in turn, optimizes the loop response.
Conventional controllers adjust linear and non-variable systems over time because of the way they are designed. This approach is useful when operating conditions are fixed with little to no hindrances or changes. However, as soon as these conditions change, conventional controllers stop working. Adaptive control, on the other hand, adapts to changing control parameters and has the ability to control the process.
Adaptive control relies on parameter estimation, which is a part of system identification. There two methods to estimate the parameters:
The Programmed Adaptive Control adjusts the controlling parameters based on the measurement of an auxiliary variable and information about the operating conditions of the process. It is often compared to feed-forward compensation, as there is no feedback to check the reliability of adaptation.
The Self-Adaptive Control is based on feedback compensation because the parameters are measured on the basis of close-loop performance with the goal to optimize it.
The main reason for using adaptive control is that most processes are nonlinear. The conventional controller is only able to maintain control loops that are designed to maintain the control variable at a set point, but once the process starts to operate beyond such variables, the changes in the functionality can be carried out by adaptive control. A change in the nature of inputs or changes in transfer function due to variations in parameters or coefficients can cause the conventional controller to cease working efficiently, justifying the need for adaptive control.