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Adaptive control of a class of nonlinear time-varying systems with multiple models 被引量:2
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作者 Koshy GEORGE Karpagavalli SUBRAMANIAN 《Control Theory and Technology》 EI CSCD 2016年第4期323-334,共12页
The adaptive control of nonlinear systems that are linear in the unknown but time-varying parameters are treated in this paper. Since satisfactory transient performance is an important factor, multiple models are requ... The adaptive control of nonlinear systems that are linear in the unknown but time-varying parameters are treated in this paper. Since satisfactory transient performance is an important factor, multiple models are required as these parameters change abruptly in the parameter space. In this paper we consider both the multiple models with switching and tuning methodology as well as multiple models with second level adaptation for this class of systems. We demonstrate that the latter approach is better than the former. 展开更多
关键词 Nonlinear time-varying systems adaptive control multiple models
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Introducing robustness in model predictive control with multiple models and switching
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作者 Sachin PRABHU Koshy GEORG 《Control Theory and Technology》 EI CSCD 2014年第3期284-303,共20页
Model predictive control is model-based. Therefore, the procedure is inherently not robust to modelling uncertainties. Further, a crucial design parameter is the prediction horizon. Only offline procedures to estimate... Model predictive control is model-based. Therefore, the procedure is inherently not robust to modelling uncertainties. Further, a crucial design parameter is the prediction horizon. Only offline procedures to estimate an upper bound of the optimal value of this parameter are available. These procedures are computationally intensive and model-based. Besides, a single choice of this horizon is perhaps not the best option at all time instants. This is especially true when the control objective is to track desired trajectories. In this paper, we resolve the issue by a time-varying horizon achieved by switching between multiple model-predictive controllers. The stability of the overall system is discussed. In addition, an introduction of multiple models to handle modelling uncertainties makes the overall system robust. The improvement in performance is demonstrated through several examples. 展开更多
关键词 Receding horizon control Time-varying horizon Multiple models SWITCHING TRACKING ROBUSTNESS
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