Dept. of Systems Engineering and Control (DISA)
Universidad Politécnica de Valencia, SPAIN
This presentation deals with the problem of control of time-delayed unstable plants. The presence of time delays is unavoidable in any real system. Usually, if the time delay is small compared with the time scale of the dynamic behavior of the plant, it can be neglected or approximate by a rational function (Padé approximation). Otherwise, it should be taken into account when designing the control. The seminal work initiated with the Smith Predictor (SP) allowed to designing the control for the delay-free plant. Unfortunately, this approach fails for unstable plants. Several extensions and modifications of the SP have been reported to deal with these plants. In this presentation, different approaches will be reviewed and some guidelines for designing the control for unstable disturbed plants, with application to the case of (MIMO) Multi_Input_Multi_Output Systems. Several examples will illustrate the design procedure and some open questions will be raised.
Department of Electrical and Computer Engineering
University of Alberta, CANADA
Abstract: In numerous real-world problems including a broad range of modeling tasks, we are faced with a diversity of locally available distributed sources of data and expert knowledge, with which one has to interact, reconcile and form a global and user-oriented model of the system under consideration. While the technology of Computational Intelligence has been playing a vital role with this regard, there are still a number of challenges inherently manifesting in these problems when dealing with efficient fusion of locally sources knowledge.
To prudently address these problems, in this talk, we introduce a concept of information granules embracing a plethora of formal constructs such as intervals (sets), fuzzy sets, rough sets, etc. We highlight an emergence of higher type and higher order information granules in the analysis and synthesis of granular models. The fundamental problem that becomes central to all investigations is concerned with the formation of information granules. We elaborate on the principle of justifiable granularity and discuss its role as a key design vehicle facilitating a formation of information granules realized on a basis of available experimental evidence (which could be either numeric or granular). We present a series of representative development scenarios of hierarchical models engaging information granules of higher type and higher order.
Faculty of Civil and Environmental Engineering
Technion - Israel Institute of Technology, ISRAEL
Abstract: In this paper, a novel approach to control uncertain discrete-time linear time-invariant systems with polytopic state and control constraints is proposed. The main idea is to use interpolation. The control law has an implicit and explicit form. In the implicit form, at each time instant, at most two linear programming problems are solved on-line. In the explicit form, the control law is given as a piecewise affine and continuous function of the state. The design method can be seen as a computationally favorable alternative to optimization-based control schemes such as Model Predictive Control. Proofs of recursive feasibility and asymptotic stability are given. Several simulations demonstrate the performance, also in comparison with MPC. Ext-ensions include output feedback, LPV and time-varying systems, and ellipsoidal constraint sets.
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