ENGINEERING TRIPOS PART IIB – 2012/2013

Module 4F3 - Optimal and Predictive Control

AIMS

To introduce methods for control system design based on the optimization of an objective subject to the constraints given by the system dynamics and limits on inputs and states. To demonstrate how such control laws can be computed and implemented in practice.

LECTURE SYLLABUS

• Formulation of convex optimisation problems
• Status of theoretical results and algorithms

• What is predictive control? Importance of constraints. Flexibility of specifications. Typical applications
• Basic formulation of predictive control problem without constraints and the receding horizon concept. Comparison with unconstrained Linear Quadratic Regulator
• Including constraints in the problem formulation. Constrained convex optimization
• Guaranteeing zero steady state error
• Stability of predictive control
• Industrial case study

• Formulation of optimal control problems. Typical applications
• Optimal control with full information (dynamic programming)
• Control of Linear Systems with a quadratic objective function
• The Kalman filter and ‘LQG’ control
• Control design with an “H-infinity” criterion

OBJECTIVES

On completion of the course, students should:

• Understand the derivation and application of optimal control methods
• Appreciate the main ideas, applications and techniques of predictive control

REFERENCES

Please see the Booklist for Group F Courses for references for this module.

Last updated: September 2012