M. S. Branicky, V. S. Borkar, and S. K. Mitter. A unified framework for hybrid control: Background, model, and theory. In Proceedings of the 33rd Conference on Decision and Control, pages 4228--4234. Control Systems Society, IEEE, December 1994.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....In recent years hybrid systems got a lot of attention. This is fairly justified since the hybrid phenomenon arises increasingly with the spreading of computers and logic based apparatus that interact with the continuous world. The research work has focused on modelling this be haviour [2] . Also results in analyzing controllability, reachability [6] as well as the stability [1] have been achieved. For controller design optimal control [5] has been considered. Most of these methods re quire high computational effort and are therefore restricted in system order. Other approaches ....

M. S. Branicky, V.S. Borkar, and S.K. Mitter. A unified framework for hybrid control: Background, model, and theory. IEEE Trans. on Automatic Control, 43(1):31-45, January 1998.

....described by differential equations. Many computer controlled engineering systems are hybrid systems, for example a temperature controller for a house or the controller of an air plane. Models for hybrid systems were proposed in [2, 9, 16, 34, 35] For an approach to control of hybrid systems, see [8]. 6 Concluding remarks What has been achieved in control of discrete event systems For practical problems with logical variables discrete event systems have been formulated as mathematical models. These systems are the basic building blocks for control. Control synthesis results yield ....

M.S. Branicky, V.S. Borkar, and S.K. Mitter. A unified framework for hybrid control: Background, model, and theory. Report LIDS-P-2239, Laboratory for Information and Decision Systems, M.I.T., Cambridge, MA, 1994.

....described by differential equations. Many computer controlled engineering systems are hybrid systems, for example a temperature controller for a house or the controller of an air plane. Models for hybrid systems were proposed in [2, 9, 16, 34, 35] For an approach to control of hybrid systems, see [8]. 6. Concluding remarks What has been achieved in control of discrete event systems For practical problems with logical variables discrete event systems have been formulated as mathematical models. These systems are the basic building blocks for control. Control synthesis results yield ....

M.S. Branicky, V.S. Borkar, and S.K. Mitter. A unified framework for hybrid control: Background, model, and theory. Report LIDS-P-2239, Laboratory for Information and Decision Systems, M.I.T., Cambridge, MA, 1994.

....of the places in place invariants as variables to choose a suitable differential equations characterizing the continuous behavior. The observation of the state of these places are then used to switch the field vectors of the differential equations describing the continuous dynamic of the resources [3, 4]. This paper is organized as follows: in Section 2 we introduce the basic concepts of BPS and Petri nets. In Section 3 we introduce how a BPS can be simulated. In Section 4 the algorithms to simulate and verify the overflow of a BPS are introduced. Finally in Section 5 we present the conclusions ....

....and verify the overflow of a BPS are introduced. Finally in Section 5 we present the conclusions of this paper. 2 BASIC CONCEPTS This section presents the basic concepts of Hybrid Systems (HS) and Petri nets. The study of a such systems involves continuous dynamic, as well, discrete phenomena [4, 3]. In this work, the continuous dynamic is described by differential equations of the form: Delta v i (t) dv(t) dt = t) t 0 where v(t) is a state variable and (t) is a field vector that depends on the discrete phenomena. Definition 2.1 A BPS is a triple (U; B; R) where: 1. U = U t [ ....

M. S. Branicky, V.S. Borkar, and S.K. Mitter. A unified framework for hybrid control: background, model, and theory. Technical Report TR LIDS-P2239, Lab. for Information and Decision Systems, MIT, April 1993.

....dynamics using logic based decision rules. Only in the last 10 years has the theoretical analysis of hybrid systems (i.e. systems with both continuous dynamics and discrete logic) been pursued in a systematic fashion. A fair amount of research has been done on the modeling of hybrid systems [1, 2, 3, 4, 5, 6, 7], but only more recently has the analysis and synthesis of hybrid control laws begun to emerge in the literature. One of the main goals of this thesis is to broaden the body of knowledge concerned with hybrid systems. Toward this end we develop tools to expedite the analysis and design of hybrid ....

....X ; oe : t 0 ; T ) Sg with x the continuous state continuous and piecewise differentiable and oe the discrete state piecewise constant and right continuous at every point, such that x and oe satisfy (1.2) 1. 3) on the interval [t 0 ; T ) Other models for hybrid systems can be found in [1, 9, 2, 3, 4, 5, 6, 7] CHAPTER 1. INTRODUCTION 3 A pair of sets fZ ; J g with Z ae X and J ae S is invariant with respect to Sigma if, for every x 0 2 Z and every oe 0 2 S, any solution fx; oeg to Sigma with x(t 0 ) x 0 and oe(t 0 ) oe 0 remains in Z Theta J for all times t t 0 for which the solution is ....

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M. S. Branicky, V. S. Borkar, and S. K. Mitter. A unified framework for hybrid control: Background, model and theory. In Proc. of the 33rd Conf. on Decision and Contr., vol. 4, pp. 4228--4234, Dec. 1994.

.... 1993b) and sliding modes control laws (Bloch and Drakunov 1994) The solution proposed in this paper falls in the class of hybrid control laws, namely those employing both con tinuous dynamics and discrete logic (Tavernini 1987) Morse et al. 1992) Back et al. 1993) Brockett 1993a) (Branicky et al. 1994) . Applications of these type of control laws to nonholonomic systems can be found in (Bloch et al. 1992) Kolmanovsky et al. 1994) where global convergence to the origin is achieved in finite time; however, these controls may result in chattering in the presence of unmodeled dynamics. This paper ....

Branicky, M. S., V. S. Borkar and S. K. Mitter (1994). A unified framework for hybrid control: Background, model and theory. In: Proc. of the 33rd CDC. Vol. 4.

....particular class of hybrid control systems. This class of systems is also of interest in the study of deterministic hybrid systems, since deterministic hybrid systems can exhibit random behavior [9] This work can be compared with the work of Branicky, et al. for deterministic hybrid systems [7] [8]; our work allows less general jump rules and does not treat impulse control, but we are able to obtain very complete results for the class of systems considered. In particular, we consider infinite horizon stochastic control problems with both discounted and average cost criteria [9] 10] In ....

....We describe the abstract formulation of the problem in Section 2. Section 3 describes a convex analytic approach to the problem. Dynamic programming equations are treated in Section 4. Section 5 presents an application to a simplified manufacturing problem [12] 13] motivated by [1] 2] [8]) Section 6 deals with some generalizations and other relevant remarks. 1 Department of Mathematics, Indian Institute of Science, Bangalore 560012, India, mkg math.iisc.ernet.in 2 Electrical Engineering Department and Institute for Systems Research, University of Maryland, College Park, ....

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M. S. Branicky, V. S. Borkar and S. K. Mitter, A unified framework for hybrid control: background, model and theory, Preprint.

.... towards the construction of simulation languages for hybrid systems using object oriented principles and bond graph methods [A1] S5] Proposals for defining the general class of hybrid systems or languages for it have been made in all fields mentioned above (see for instance [GNRR] A1] S5] [BBM], BGM] Such a definition or language usually calls for the specification of a number of items: i) the laws of motion governing the continuous evolution in the intervals between events, ii) the rules that determine the event times (times at which events will take place) iii) the transition ....

....chattering will occur in which the system keeps switching between several discrete states without finding a situation in which any continuous dynamics can be active. A sufficient condition to prevent such chattering is strict separation between action sets and destination sets (see for instance [BBM]) In this paper we shall consider sufficient conditions that are of a completely different nature and that do not assume such a strict separation. Complementary slackness systems will be defined precisely below, but they may be loosely described as systems that arise from variational principles ....

M. S. Branicky, V. S. Borkar, and S. K. Mitter, A unified framework for hybrid control: background, model, and theory , Technical Report LIDS-P-2239 (revised), Lab. for Information and Decision Systems, MIT, June 1994.

....systems. These approaches abstract the differential equations by clocks [7] or differential inclusions [8] and verify the resulting abstracted system. More unified approaches in which the hybrid system design is not decoupled into the design of the individual continuous and discrete components are [9, 10, 11, 3, 12]. A natural framework for formulating problems in which many agents have different objectives is game theory [13, 14] In a game theoretic setting, each agent is modeled as a player in a noncooperative, zero sum dynamic game [15] In this framework, each agent treats every other agent as a ....

M. Branicky, V. Borkar, and S. Mitter. A unified framework for hybrid control: background, model and theory. Technical Report LIDS-P-2239, Massachusets Institute of Technology, 1994.

No context found.

M. S. Branicky, V. S. Borkar, and S. K. Mitter. A unified framework for hybrid control: Background, model, and theory. In Proceedings of the 33rd Conference on Decision and Control, pages 4228--4234. Control Systems Society, IEEE, December 1994.

No context found.

M.S. Branicky, V.S. Borkar, and S.K. Mitter. A unified framework for hybrid control: Background, model, and theory. Technical report lids-p-2239, Laboratory for Information and Decision Systems, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139-4307 USA, 1994.

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