TA 1 - 8 : 30 Adaptive Inverse Control

A plant can track an input command signal if it is driven by a controller whose transfer function approximates the inverse of its transfer function. A stable inverse can be obtained even if the plant is nonminimum-phase. No direct feedback is used, except that the plant output is monitored and utilized to adapt the parameters of the controller. A model-reference inverse control system can learn to approximate a desired reference-model dynamics. Control of internal plant disturbance is accomplished with an optimal adaptive disturbance canceller. It does not affect plant dynamics, but feeds back plant disturbance in a way that minimizes disturbance power at the plant output. Similar principles can be utilized to control nonlinear systems. Neural networks are used to build a model of the plant and to construct its “inverse”