This unit aims to firstly develop an understanding of key features of methods for mathematically modelling various categories of dynamical systems in terms of sets of dynamic and algebraic equations, ranging from engineering to biomedical systems. Secondly, you are shown how to write algorithms for efficient numerical solution of these equations. Computer-aided control systems design using optimal and robust control methods is then covered. Thirdly, you are introduced to Lyapunov and function analytic techniques for nonlinear systems stability analysis, and to nonlinear control design methods including feedback linearisation, sliding mode and passivity-based control techniques.
The minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of 3-6 hours of scheduled learning activities and 6-9 hours of independent study per week. Scheduled activities may include a combination of teacher-directed learning, peer-directed learning and online engagement. Independent study may include associated readings, assessment and preparation for scheduled activities.
Design optimal controllers and observers for both continuous-time and discrete-time dynamic systems.
Generate dynamic models using various system identification techniques/tools such as (but not limited to) step response identification, least squares and the System Identification Toolbox.
Design and simulate controllers and observers using computer-aided tools.
Discern the need for life-long learning about advanced control technique.
Analyse robustness of uncertain systems and to suggest suitable controller structures.
Use various methods to design controllers and observers for nonlinear systems, such as (but not limited to) feedback linearisation, diffeomorphism, and Linear Matrix Inequalities.
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