Continuity of dynamical systems: A system theoretic approach

This paper studies continuity of linear time-invariant dynamical systems, defined in terms of the system’s behavior. This concept is related to parameter continuity of associated system representations. For the case at hand, these will be autoregressive (AR) representations. The main result states that a family of linear time-invariant systems, with uniformly bounded dimension of the state space, converges if and only if the systems admit a convergent full rank (AR) representation.     

The contact problem for linear continuous-time dynamical systems: ageometric approach

In this paper linear time-invariant dynamical systems described by a combination of differential equalities and static inequalities in state-space formulation are investigated. Of special interest is the contact problem: the effect of the boundary of the constraint set on the behavior of the system. This effect is studied by dividing the state-space in a number of disjunct subsets. It is shown that these subsets are invariant under linear state feedback. In our framework, a specific place is reserved for modeling the laws of collision, i.e., physical modeling, which are regarded as external factors. Our main results are a system theoretical framework in which we describe what happens upon contact and a definition of the constrained state-space system in terms of its restricted behavior. The results presented here can be considered as an extension for restricted linear systems of the classic positive invariance theory for linear systems     

Bisimilar linear systems

The notion of bisimulation in theoretical computer science is one of the main complexity reduction methods for the analysis and synthesis of labeled transition systems. Bisimulations are special quotients of the state space that preserve many important properties expressible in temporal logics, and, in particular, reachability. In this paper, the framework of bisimilar transition systems is applied to various transition systems that are generated by linear control systems. Given a discrete-time or continuous-time linear system, and a finite observation map, we characterize linear quotient maps that result in quotient transition systems that are bisimilar to the original system. Interestingly, the characterizations for discrete-time systems are more restrictive than for continuous-time systems, due to the existence of an atomic time step. We show that computing the coarsest bisimulation, which results in maximum complexity reduction, corresponds to computing the maximal controlled or reachability invariant subspace inside the kernel of the observations map. These results establish strong connections between complexity reduction concepts in control theory and computer science.     

Aggregation of a class of interconnected, linear dynamical systems

In this paper, we introduce the notion of a “meaningful” average of a collection of dynamical systems as distinct from an “ensemble” average. Such a notion is useful for the study of a variety of dynamical systems such as traffic flow, power systems, and econometric systems. We also address the associated issue of the existence and computation of such an average for a class of interconnected, linear, time invariant dynamical systems. Such an “average” dynamical system is not only attractive from a computational perspective, but also represents the average behavior of the interconnected dynamical systems. The problem of analysis and control of heirarchical, large scale control systems can be simplified by approximating the lower level dynamics of such systems with such an average dynamical system.     

Reachability of linear switched systems: Differential geometric approach

The paper investigates the structure of the reachable set of linear switched systems. The structure of the reachable set is determined using techniques from classical nonlinear systems theory, namely, the theory of orbits developed by H. Sussman and the realization theory for nonlinear systems developed by B. Jakubczyk.     

Discerning controllers for switching linear systems: Existence and genericity

This paper presents recent developments in the study of non-autonomous switching linear systems. For such systems, we address the issue of how to systematically design linear controllers allowing the active process mode to be observable from closed-loop data. The results are stated formally by introducing the notion of discerning controllers. Both existence and genericity problems are discussed. It is finally shown how a given family of discerning controllers can be implemented as a single hybrid system which preserves the discerning capability of the original controllers. Examples are discussed to substantiate the analysis.     

Stochastic model predictive control for constrained discrete-time Markovian switching systems

In this paper we study constrained stochastic optimal control problems for Markovian switching systems, an extension of Markovian jump linear systems (MJLS), where the subsystems are allowed to be nonlinear. We develop appropriate notions of invariance and stability for such systems and provide terminal conditions for stochastic model predictive control (SMPC) that guarantee mean-square stability and robust constraint fulfillment of the Markovian switching system in closed-loop with the SMPC law under very weak assumptions. In the special but important case of constrained MJLS we present an algorithm for computing explicitly the SMPC control law off-line, that combines dynamic programming with parametric piecewise quadratic optimization.     

Regularizability of complex switched server queueing networks modelled as hybrid dynamical systems

The paper considers the problem of the qualitative analysis of complex switched server queueing networks. Such networks can be used to model various flexible manufacturing, communications, and computer systems. We introduce the concept of regularizability for such systems and obtain a necessary and sufficient condition for a switched server queueing network to be regularizable.     

On the controllability of switching linear systems

This note presents a necessary and sufficient condition for small time controllability of a linear switching system (that is, a collection of linear time-invariant control systems, where a trajectory is any concatenation of trajectories of the individual systems). This result extends the controllability condition recently obtained for unconstrained linear switching systems to the case of control which is constrained in a cone.     

Stabilizing adaptive controller for uncertain dynamical systems: An LMI approach

Adaptive stabilization of a class of linear systems with matched and unmatched uncertainties is considered in this paper. The proposed controller indeed stabilizes the uncertain system for any positive values of its non-adaptive gain that may be tuned to enhance dynamic response of system. The performance of uncertain system along with the Algebraic Riccati Equation that arises from the adaptive stabilizing controller is now formulated as a multi-objective Linear Matrix Inequality optimization problem. The decay rate and a factor governing the ultimate bound of the system states are considered to characterize the closed loop system performance. Finally, the effectiveness of the proposed controller is illustrated via stabilizing a mass-spring system. Recommended by Editorial Board member Gang Tao under the direction of Editor Young Il Lee. The authors would like to thank the reviewers for their valuable comments and suggestions that have improved the quality of this paper. Sandip Ghosh received the B.E. in Electrical Engineering from Bengal Engineering College (D.U.), Howrah, and Master in Control System Engineering from Jadavpur University, Kolkata, India, in 1999 and 2003 respectively. Presently he is pursuing the Ph.D. degree at Indian Institute of Technology, Kharagpur, India. His research interests include adaptive control, robust control and control of time-delay systems. Sarit K. Das is a Professor of Electrical Engineering Department, Indian Institute of Technology, Kharagpur, India. He received the Ph.D. degree in 1985 from the same department. His research interests include design of periodic controller, decoupling of multivariable systems, modeling and robust control of complex systems. Goshaidas Ray is a Professor of Electrical Engineering Department, Indian Institute of Technology, Kharagpur, India. He received the Ph.D. degree in 1982 from Indian Institute of Technology Delhi, India. His research interests include modeling, estimation, model-based control, intelligent control, robotic systems and distributed control systems.     

A control problem for affine dynamical systems on a full-dimensional polytope

Given an affine system on a full-dimensional polytope, the problem of reaching a particular facet of the polytope, using continuous piecewise-affine state feedback is studied. Necessary conditions and sufficient conditions for the existence of a solution are derived in terms of linear inequalities on the input vectors at the vertices of the polytope. Special attention is paid to affine systems on full-dimensional simplices. In this case, the necessary and sufficient conditions are equivalent and a constructive procedure yields an affine feedback control law, that solves the reachability problem under consideration.     

The human side of systems: an experiential approach

Research is presented on the effect of human relations training on the interpersonal orientation of information systems professionals. The results indicate that training can make a difference.Interpersonal orientation is significant because the more systems professionals can effectively express their feelings on substantive issues and help others to do so, the more likely they are to be effective in problem solving and decision making. Increased effectiveness is a meaningful step towards the important goal of effective management information systems that truly meet the needs of their users.     

Matching, linear systems, and the ball and beam

A recent approach to the control of underactuated systems is to look for control laws which will induce some specified structure on the closed loop system. In this paper, we describe one matching condition and an approach for finding all control laws that fit the condition. After an analysis of the resulting control laws for linear systems, we present the results from an experiment on a nonlinear ball and beam system.     

Root-mean-square gains of switched linear systems: A variational approach

We consider the problem of computing the root-mean-square (RMS) gain of switched linear systems. We develop a new approach which is based on an attempt to characterize the “worst-case” switching law (WCSL), that is, the switching law that yields the maximal possible gain. Our main result provides a sufficient condition guaranteeing that the WCSL can be characterized explicitly using the differential Riccati equations (DREs) corresponding to the linear subsystems. This condition automatically holds for first-order SISO systems, so we obtain a complete solution to the RMS gain problem in this case.     

Estimators for linear dynamical SISO systems with disturbed input-output measurements

Several types of instrumental variable estimators are proposed for estimating parameters of linear dynamical single-input single-ouput systems with disturbed input-output measurements.No restrictions on the colouring of the distributions are imposed. The availability of extra (disturbed) measurements of input or output data simpifies the choice of the instrumental variable.     

Realization theory for linear switched systems: Formal power series approach

The paper deals with the realization theory of linear switched systems. Necessary and sufficient conditions are formulated for a family of input–output maps to be realizable by linear switched systems. Characterization of minimal realizations is presented. The paper treats two types of linear switched systems. The first one is when all switching sequences are allowed. The second one is when only a subset of switching sequences is admissible, but within this restricted set the switching times are arbitrary. The paper uses the theory of formal power series to derive the results on realization theory.     

On the constrained small-time controllability of linear systems

This note presents a necessary and sufficient condition for small-time controllability of a linear system with respect to a cone. This result extends the controllability conditions for linear systems to the case of control and phase constraints.     

A control design method for a class of switched linear systems

In this note we consider the stability properties of a system class that arises in the control design problem of switched linear systems. The control design we are studying is based on a classical pole-placement approach. We analyse the stability of the resulting switched system and develop analytic conditions which reduce the complexity of the stability problem. We further consider two special cases for which strongly simplified conditions are obtained that support the analytic controller design.     

Clustering categorical data: an approach based on dynamical systems

We describe a novel approach for clustering collections of sets, and its application to the analysis and mining of categorical data. By “categorical data,” we mean tables with fields that cannot be naturally ordered by a metric – e.g., the names of producers of automobiles, or the names of products offered by a manufacturer. Our approach is based on an iterative method for assigning and propagating weights on the categorical values in a table; this facilitates a type of similarity measure arising from the co-occurrence of values in the dataset. Our techniques can be studied analytically in terms of certain types of non-linear dynamical systems. Received February 15, 1999 / Accepted August 15, 1999