Titlebook: Assessment and Future Directions of Nonlinear Model Predictive Control; Rolf Findeisen,Frank Allg?wer,Lorenz T. Biegler Book 2007 Springer

Detrusor-Muscle

書(shū)目名稱(chēng)Assessment and Future Directions of Nonlinear Model Predictive Control影響因子(影響力)




書(shū)目名稱(chēng)Assessment and Future Directions of Nonlinear Model Predictive Control影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Assessment and Future Directions of Nonlinear Model Predictive Control網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Assessment and Future Directions of Nonlinear Model Predictive Control網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Assessment and Future Directions of Nonlinear Model Predictive Control被引頻次




書(shū)目名稱(chēng)Assessment and Future Directions of Nonlinear Model Predictive Control被引頻次學(xué)科排名




書(shū)目名稱(chēng)Assessment and Future Directions of Nonlinear Model Predictive Control年度引用




書(shū)目名稱(chēng)Assessment and Future Directions of Nonlinear Model Predictive Control年度引用學(xué)科排名




書(shū)目名稱(chēng)Assessment and Future Directions of Nonlinear Model Predictive Control讀者反饋




書(shū)目名稱(chēng)Assessment and Future Directions of Nonlinear Model Predictive Control讀者反饋學(xué)科排名

MIME

原始

Conditions for MPC Based Stabilization of Sampled-Data Nonlinear Systems Via Discrete-Time Approximato be computed by the receding horizon control method based on discrete-time approximate models. Multi-rate — multistep control is considered and both measurement and computational delays are allowed. It is shown that the same family of controllers that stabilizes the approximate discrete-time model

你正派

琺瑯

The Potential of Interpolation for Simplifying Predictive Control and Application to LPV Systemse of trading off performance for online computational simplicity. It is then shown how these can be extended to linear parameter varying systems, with a relatively small increase in the online computational requirements. Some illustrations are followed with a brief discussion on areas of potential d

擁護(hù)者

Techniques for Uniting Lyapunov-Based and Model Predictive Controltion level (Hybrid predictive control) and at the design level (Lyapunov-based predictive control) in a way that allows for an explicit characterization of the set of initial conditions starting from where closed-loop stability is guaranteed in the presence of constraints.

離開(kāi)真充足

Morose

Model Predictive Control for Nonlinear Sampled-Data Systemsaws. The given continuous-time feedback controller is used to generate a reference trajectory which we track numerically using a sampled-data controller via an MPC strategy. Here our goal is to minimize the mismatch between the reference solution and the trajectory under control. We summarize the ne

Mindfulness

Sampled-Data Model Predictive Control for Nonlinear Time-Varying Systems: Stability and Robustnessas well as the computation of the control laws, are carried out at discrete instants of time. This framework can address a very large class of systems, nonlinear, time-varying, and nonholonomic..As in many others sampled-data Model Predictive Control schemes, Barbalat’s lemma has an important role i

欲望