Publication Type:E. Conference Papers
Source:Assessment and Future Directions of Nonlinear Model Predictive Control, Springer Berlin / Heidelberg, Volume Lecture Notes in Control and Information Sciences 358, Issue NULL, p.17–34 (2007)
Abstract:The robustness of asymptotic stability with respect to measurement noise for discrete-time feedback control systems is discussed. It is observed that, when attempting to achieve obstacle avoidance or regulation to a disconnected set of points for a continuous-time system using sample and hold state feedback, the noise robustness margin necessarily vanishes with the sampling period. With this in mind, we propose two modifications to standard model predictive control (MPC) to enhance robustness to measurement noise. The modifications involve the addition of dynamical states that make large jumps. Thus, they have a hybrid flavor. The proposed algorithms are well suited for situations where control algorithms must respond quickly to large changes in operating conditions but not be easily confused by moderately large measurement noise and similar disturbances.