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This article studies the problems of stability analysis and controllers design for continuous-time linear systems with the consideration of full state saturation as well as partial state saturation. Owing to the difficulty and complexity in the controller design under state saturation, a new and tractable system is constructed, and it is shown that the constructed system is with the same domain of attraction as the original system. Based on this property, an linear matrix inequality (LMI) based method is presented for estimating the attraction domain of the origin for the new constructed system with state saturation. In addition, an algorithm is developed for designing dynamic output-feedback controllers, which guarantee that the attraction domain of the origin for the closed-loop system is as 'large' as possible. An example is given to illustrate the effectiveness of the design method. [ABSTRACT FROM AUTHOR]

This study addresses a new digital redesign (DR) problem for a linear time-invariant (LTI) system with a perturbation that is an uncertain non-linear time-varying function but linearly bounded. Given a continuous-time linear controller robustly stabilising the origin of the perturbed system for all admissible perturbations, the concerned DR problem is to design the sampled-data linear controller making trajectories of the continuous-time and the sampled-data non-linear control systems close, or at least robustly stabilising the perturbed system. The proposed approach interprets the DR problem as the stabilisation problem considering the convergence rate for error dynamics between the continuous-time and the sampled-data non-linear control systems. Sufficient conditions for the stabilisation are derived and formulated in the form of linear matrix inequalities (LMIs). A numerical example is used to demonstrate the effectiveness of the proposed design technique. [ABSTRACT FROM AUTHOR]

An integrated batch-to-batch control and within-batch online control strategy for tracking product quality trajectories in batch processes is proposed. On the basis of a batch-wise linear time-varying perturbation model, iterative learning control (ILC) is implemented for batch-to-batch control and the convergence of tracking errors under ILC is guaranteed. Within a batch, a predictive model is constructed by directly partitioning the linear time-varying model according to time, then batch model predictive control with shrinking horizons is applied online to reduce the effects of model-plant mismatch and/or unknown disturbances. By properly combining these two control methods, the integrated control strategy can complement both methods to obtain good performance. The proposed strategy is demonstrated on a simulated batch polymerisation process, and the results show that the performance can be improved quite significantly under the integrated control strategy than only under ILC, especially when disturbances occur. [ABSTRACT FROM AUTHOR]

The authors present an enhanced composite nonlinear feedback (CNF) control technique for discrete-time systems with input saturation and with external disturbances. The conventional CNF control is proven to be capable of yielding better transient performance in tracking control for systems with input saturation. However, when the given system has external disturbances as in most practical situations, the conventional CNF control yields some steady-state errors in the resulting output response. The enhanced CNF technique presented is an extension of the conventional one. It retains the good transient properties of the conventional CNF control and at the same time has the additional capacity for eliminating steady-state bias because of unknown constant disturbances. A numerical example and practical disk drive servo system design are provided to demonstrate the effectiveness of this control technique. Experimental results show that the new design yields a huge improvement over classical approaches. [ABSTRACT FROM AUTHOR]