Robust Smith Predictor Design for Time-Delay Systems with H∞ Performance

A new method for robust fixed-order H∞ controller design for uncertain time-delay systems is presented. It is shown that the H∞ robust performance condition can be represented by a set of convex constraints with respect to the parameters of a linearly parameterized primary controller in the Smith predictor structure. Therefore, the parameters of the primary controller can be obtained by convex optimization. The proposed method can be applied to stable SISO and MIMO models with uncertain dead-time and with multimodel and frequency-dependent uncertainty. It is also shown that how the design method can be extended to unstable SISO models. The design of robust gain-scheduled dead-time compensators is also investigated. The performance of the method is illustrated for both SISO and MIMO systems by simulation examples

Robustness analysis of discrete predictor-based controllers for input-delay systems

In this article, robustness to model uncertainties are analysed in the context of discrete predictor-based state-feedback controllers for discrete-time input-delay systems with time-varying delay, in an LMI framework. The goal is comparing robustness of predictor-based strategies with respect to other (sub)optimal state feedback ones. A numerical example illustrates that improvements in tolerance to modelling errors can be achieved by using the predictor framework.The authors are grateful for grant nos. DPI2008-06737-C02-01, DPI2008-06731-C02-01, DPI2011-27845-C02-01 and PROMETEO/2008/088 from the Spanish and Valencian governments.González Sorribes, A.; Sala, A.; García Gil, PJ.; Albertos Pérez, P. (2013). Robustness analysis of discrete predictor-based controllers for input-delay systems. International Journal of Systems Science. 44(2):232-239. https://doi.org/10.1080/00207721.2011.600469S232239442Boukas, E.-K. (2006). 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Robust predictive control strategy applied for propofol dosing using BIS as a controlled variable during anesthesia

This paper presents the application of predictive control to drug dosing during anesthesia in patients undergoing surgery. The performance of a generic predictive control strategy in drug dosing control, with a previously reported anesthesia-specific control algorithm, has been evaluated. The robustness properties of the predictive controller are evaluated with respect to inter- and intrapatient variability. A single-input (propofol) single-output (bispectral index, BIS) model of the patient has been assumed for prediction as well as for simulation. A set of 12 patient models were studied and interpatient variability and disturbances are used to assess robustness of the controller. Furthermore, the controller guarantees the stability in a desired range. The applicability of the predictive controller in a real-life environment via simulation studies has been assessed

Interpolation Based Controller for Trajectory Tracking in Mobile Robots

In this work, a novel algorithm for trajectory tracking in mobile robots is presented. For the purpose of tracking trajectory, a methodology based on the interpolation of trigonometric functions of the wheeled mobile robot kinematics is proposed. In addition, the convergence of the interpolation-based control systems is analysed. Furthermore, the optimal controller parameters are selected through Monte Carlo Experiments (MCE) in order to minimize a cost index. The MCE is able to find, the best set of gains that minimizes the tracking error. Experimental results over a mobile robot Pionner 3AT are conclusive and satisfactory. In addition, a comparative study of control performance is carried out against another controllers. © 2016, Springer Science+Business Media Dordrecht