This course presents the principles of closed-loop control system design when physics-based models of the open-loop plant (derived previously, see 2201304) are available. The course focuses on designing controllers suitable for achieving desired (and often contradictory) control objectives such as minimized steady-state error, improved stability and user-defined shaping of transient system response in closed-loop. For this purpose, traditional controllers are reviewed, basic tools for assessing the controlled system stability and transient response are given, and specific techniques for controller design based on transfer function and state-space representations are presented in detail.
- Performance and robustness characteristics of closed-loop systems, comparison with open-loop systems.
- Steady state errors and stability in closed-loop representations, part I: Computing steady state errors, the influence of open-loop system type on steady state error, hints on the trade-off between closed-loop errors and stability.
- Steady state errors and stability in closed-loop representations, part II: Stability assessment via the Routh criterion, the trade-off between closed-loop errors and stability revisited.
- The root locus method: Closed-loop stability evaluation, controller design for transient response shaping and steady state error minimization.
- The method of characteristic polynomial matching: Analytical controller design for transient response shaping and steady state error minimization, hints on reference model matching.
- Bode and Nyquist plots revisited: Assessment of closed-loop stability and margins, hints on controller design.
- System representation in State-Space, part I: The concept of state-space representation versus transfer functions, system eigenvalues and eigenvectors.
- System representation in State-Space, part II: Solution of state-space equations via Laplace or eigenvalues/eigenvectors, hints on closed-loop pole placement for achieving desired closed-loop performance.