Sampled data systems and generating functions

Application of Z-transforms to sampled-data system

3 sampled-data control of nonlinear systems

This chapter provides some of the main ideas resulting from recent developments in sampled-data control of nonlinear systems. We have tried to bring the basic parts of the new developments within the comfortable grasp of graduate students. Instead of presenting the more general results that are available in the literature, we opted to present their less general versions that are easier to understand and whose proofs are easier to follow. We note that some of the proofs we present have not appeared in the literature in this simplified form. Hence, we believe that this chapter will serve as an important reference for students and researchers that are willing to learn about this area of research

Quantized Feedback Stabilization of Sampled-Data Switched Linear Systems

We propose a stability analysis method for sampled-data switched linear systems with quantization. The available information to the controller is limited: the quantized state and switching signal at each sampling time. Switching between sampling times can produce the mismatch of the modes between the plant and the controller. Moreover, the coarseness of quantization makes the trajectory wander around, not approach, the origin. Hence the trajectory may leave the desired neighborhood if the mismatch leads to instability of the closed-loop system. For the stability of the switched systems, we develop a sufficient condition characterized by the total mismatch time. The relationship between the mismatch time and the dwell time of the switching signal is also discussed.Comment: 17 pages, 3 figure

Sampled data systems passivity and discrete port-Hamiltonian systems

In this paper, we present a novel way to approach the interconnection of a continuous and a discrete time physical system first presented in [1][2] [3]. This is done in a way which preserves passivity of the coupled system independently of the sampling time T. This strategy can be used both in the field of telemanipulation, for the implementation of a passive master/slave system on a digital transmission line with varying time delays and possible loss of packets (e.g., the Internet), and in the field of haptics, where the virtual environment should `feel¿ like a physical equivalent system

Compensation of sampled-data systems

"November 8, 1958.""Reprinted from Proceedings of the National Electronics Conference, Volume XIII, Hotel Sherman, Chicago, Illinois, October 7, 8, 9, 1957.""Compensation of sampled-data systems is straight forward if the compensation network can be separated from the rest of the system by samplers. However, use of directly connected continuous networks presents more of a problem. Existing theory does not adequately cover such compensation. This paper examines the above situation using z-transform theory and continuous network realizability conditions. Lack of a general correlation between the number of z-plane and s-plane zeros presents the major problem. This difficulty becomes apparent when attempting to find a principle Laplace transform for the final system impulse response following z-plane compensation. By imposing certain restrictions on z-plane pole locations and by approximating the desired system impulse response in the s-plane, this paper demonstrates the use of directly connected RC networks in lieu of discrete networks or digital computers for compensating sampled-data systems. Studies are, also, made concerning the requirements necessary to eliminate the need for approximating the final impulse response. Graphs are presented to allow the solution of this problem for third order systems."--Page 1

Model Reduction for Aperiodically Sampled Data Systems

Two approaches to moment matching based model reduction of aperiodically sampled data systems are given. The term "aperiodic sampling" is used in the paper to indicate that the time between two consecutive sampling instants can take its value from a pre-specified finite set of allowed sampling intervals. Such systems can be represented by discrete-time linear switched (LS) state space (SS) models. One of the approaches investigated in the paper is to apply model reduction by moment matching on the linear time-invariant (LTI) plant model, then compare the responses of the LS SS models acquired from the original and reduced order LTI plants. The second approach is to apply a moment matching based model reduction method on the LS SS model acquired from the original LTI plant, and then compare the responses of the original and reduced LS SS models. It is proven that for both methods, as long as the original LTI plant is stable, the resulting reduced order LS SS model of the sampled data system is quadratically stable. The results from two approaches are compared with numerical examples