An Approach to Adaptive Control Using Real Time Identification

An adaptive controller consisting of a real time identifier and a minimum variance regulator is discussed. The identification is done by augmenting the state with the unknown parameters of the process. This usually leads to a non-linear filtering problem. By choosing a model of special structure the problem can, however, be reduced to a linear problem. The control law is derived using stochastic optimal control theory. By choosing a special criterion, the stochastic control problem can be solved analytically. The behaviour of the adaptive controller is illustrated in two examples.