Identification and adaptive control
C S Berger
6 points * 39 hours of lectures and practical work * Irregular availability * Clayton
Objectives To provide an understanding of the relationships between mathematical models used to describe the performance of dynamic systems. To enable the student to derive mathematical models from measured plant data and to design adaptive controllers.
Synopsis Mathematical models: state space equations, transfer functions, continuous and discrete time systems. Identification methods: recursive least squares, instrument variables and generalised least squares, time-varying systems, non-linear systems, experimental design. Adaptive control: minimum variance, pole-placement, predictive control, optimal control.
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