Sampled-data integral control of multivariable linear infinite-dimensional systems with input nonlinearities

Adaptive sampled-data integral control of stable infinite-dimensional linear systems

In this paper, adaptive discrete-time low-gain integral control strategies are presented for tracking constant reference signals for infinite-dimensional discrete-time power-stable linear systems. The discrete-time results are applied in the development of adaptive sampled-data low-gain integral control of well-posed infinite-dimensional exponentially stable linear systems. Our results consider...

Discrete-Time and Sampled-Data Low-Gain Control of Infinite-Dimensional Linear Systems in the Presence of Input Hysteresis

We introduce a general class of causal dynamic discrete-time nonlinearities which have certain monotonicity and Lipschitz continuity properties. In particular, the discretizations of a large class of continuous-time hysteresis operators obtained by applying the standard sampling and hold operations belong to this class. It is shown that closing the loop around a power-stable, linear, infinite-d...

Stability of Infinite-dimensional Sampled-data Systems

Suppose that a static-state feedback stabilizes a continuous-time linear infinite-dimensional control system. We consider the following question: if we construct a sampled-data controller by applying an idealized sample-andhold process to a continuous-time stabilizing feedback, will this sampled-data controller stabilize the system for all sufficiently small sampling times? Here the state space...

Adaptive low-gain integral control of linear systems with input and output nonlinearities

An adaptive low-gain integral control framework is developed for tracking constant reference signals in a context of nite-dimensional, asymptotically stable, single-input, single-output linear systems subject to locally Lipschitz, monotone input and output nonlinearities of a general nature: the input nonlinearity is required to satisfy an asymptotic growth condition (of suucient generality to ...

Low-gain integral control of continuous-time linear systems subject to input and output nonlinearities