Robust control

Robust control is a branch of control theory that explicitly deals with uncertainty in its approach to controller design. Robust control methods are designed to function properly so long as uncertain parameters or disturbances are within some (typically compact) set. Robust methods aim to achieve robust performance and/or stability in the presence of bounded modelling errors.

In contrast with adaptive control, a robust control policy is static; rather than adapting to measurements of variations, the controller is designed to work assuming that certain variables will be unknown but, for example, bounded. The early methods of Bode and others were fairly robust; the state-space methods invented in the 1960's and 1970's were sometimes found to lack robustness, prompting research to improve them.

Examples

• High-gain feedback is a simple example of a robust control method; with sufficiently high gain, any parameter variations will be negligible. High-gain feedback is the principle that allows simplified models of operational amplifiers and emitter-degenerated bipolar transistors to be used in a variety of different settings.

• A modern example of a robust control technique is H-infinity loop-shaping, which was developed by Duncan McFarlane and Keith Glover of Cambridge University; this method minimizes the sensitivity of a system over its frequency spectrum, and this guarantees that the system will not greatly deviate from expected trajectories when disturbances enter the system.

References

• Ray, L.R. (1991). "Stochastic Robustness of Linear-Time-Invariant Control Systems" (PDF). IEEE Trans. Automatic Control. 36 (1): 82–87. {{cite journal}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)

See also

• Control theory
• Control engineering
• Fractional order control
• H-infinity control
• H-infinity loop-shaping
• Sliding mode control
• Intelligent control
• Process control
• Root locus
• Servomechanism
• Stable polynomial
• State space (controls)
• System identification