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Ali Khaki-Sedigh,Peyman Bagheri 제어·로봇·시스템학회 2015 International Journal of Control, Automation, and Vol.13 No.1
Many industrial processes can be effectively described with first-order plus fractional dead time models. In the case of plants with a large dead time relative to the time constant, approximations in discretizing the time delay can adversely affect the performance and if the sample time is enforced by system requirements, the fractional nature of the delay should be considered. In this paper, an analytical approach to model predictive control tuning for stable and unstable first-order plus dead time models with fractional delay is presented. The existing tuning methods are based on trial and error or numerical optimization approaches and the available closed form equations are limited to plants with integer delays. In this paper, an analytical approach is adopted and the issues of closed loop stability and achievable performance are addressed. Finally, simulation results are used to show the effective-ness of the proposed tuning strategy.
Robust H∞ Filtering for Uncertain Discrete-time Descriptor Systems
Sahere Beidaghi,Ali Akbar Jalali,Ali Khaki-Sedigh,Bijan Moaveni 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.3
This paper considers the robust H∞ filtering problem for uncertain discrete-time descriptor systems. Aclass of uncertain systems with norm-bounded uncertainties is considered. The necessary and sufficient conditionfor solvability of the robust full-order H∞ filtering is introduced which is generally less conservative than thoseexisting sufficient conditions only. Explicit expressions of these filters are given. In addition to the full-orderfiltering problem, the robust reduced-order H∞ filtering is also addressed by using slack variables technique in newsufficient conditions. The parameters of reduced-order filters are directly extracted from the solvability conditions. All the above conditions are convex and are expressed in term of linear matrix inequalities (LMIs) by using theoriginal system matrices. The results generalize the previously developed H∞ filter design for standard discretetimesystems. A numerical example is presented to demonstrate the effectiveness of the proposed approaches.
New H2 Filtering for Descriptor Systems: Singular and Normal Filters
Sahereh Beidaghi,Ali Akbar Jalali,Ali Khaki-Sedigh 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.1
This paper considers the H2 filtering problem for continuous-time descriptor systems by revisiting the H2performance and introducing the new formulation. Differing from previous results, recent note provides solvabilityconditions of the H2 filtering problem with both the singular and the normal filters. The results are introduced asnecessary and sufficient conditions for the singular filters and as sufficient conditions for the normal filters. Theseconditions are extracted without decomposing the original system matrices and are expressed in terms of strict linearmatrix inequalities (LMIs). A numerical example with simulation results is given to illustrate the effectiveness ofthe proposed methods.
Seyed Hamid Hashemipour,Nastaran Vasegh,Ali Khaki-Sedigh 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.3
This paper investigates the problem of decentralized model reference adaptive control (MRAC) for aclass of stable large scale interconnected systems. The interconnections are nonlinear with time varying delayswhich are bounded by polynomials with unknown gains. Also, it is assumed that both state and input delays arepresent. To overcome the input delay effect, a nested predictor based approach is adopted to predict the future states. The uniformly bounded stability of the closed loop system is proved by employing a suitable Lyapunov function. The effectiveness of the proposed approaches is illustrated by a numerical example.
Passivity-Based Structured Model Predictive Control with Guaranteed Stability
Ghazal Montaseri,Mohammad Javad Yazdanpanah,Ali Khaki-Sedigh 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
In this paper, a model predictive control scheme for a class of nonlinear systems is presented. In the proposed algorithm, the new cost function for MPC is defined. This cost function is inspired by the structure of passivity-based control. By simple tuning of weighting matrices, the asymptotic stability is guaranteed. Moreover, a closed-form solution to the optimal control problem is calculated via representing the nonlinear system in the state-dependent coefficient form of the state-space model. This point is of great importance in online applications. To demonstrate its efficiency, the passivity-based structured MPC is applied to control a rotational motion of a rigid body.