4. Indirect model reference adaptive control

Indirect adaptive control is when the controller estimates the plant to predict its state variables and these are used to modify the controller parameters.

Direct adaptive control is when there is no plant identification, instead the controller parameters are modified on the basis of the error the system has with the reference.

MRAC is a direct adaptive control method (refer Figure 2), however in this chapter we shall be taking a mixed approach to the problem.

In MRAC we define a reference model that responds to the input signal (r) as we would like our plant to respond. The controller generates a control signal (u) based on its control law which it expects will make the plant output (y) follow the reference output (yref). Depending on the deviation (or error), the adjustment mechanism will update the control law (by modifying parameters) of the controller. This process is repeated iteratively so that the plant follows the reference.

The beauty of the approach taken in this chapter is that we needn't formalize the control logic. We will delve deeper into neural networks before returning to the problem at hand. For the

Figure 2. MRAC block diagram. Image courtesy of Wikipedia under CC license.

time being we will leave the 'reference model, 'adjustment mechanism' and the 'controller' as black boxes, they will be revisited in Section 6.
