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The paper discusses connexions between optimality and passivity-like properties in discrete-time. The problem is set in the framework of differential/difference representations of discrete-time dynamics. The Hamilton Jacobi Bellman equality is specified and the optimal control is implicitly described. Some particular cases for which explicit control solutions can be built are analyzed. An example concludes the paper. [ABSTRACT FROM PUBLISHER]

In this paper, the performances of a digital back-stepping stabilizing control strategy are tested on a real plant. This method applies to continuous-time systems in strict feedback forms which admit a stabilizing backstepping controller. Simulation and experimental results illustrate the benefits of the proposed digital strategy with respect to emulated solutions. References tracking is achieved with less control effort even when considering large sampling periods. [ABSTRACT FROM PUBLISHER]

For continuous-time linear time-invariant systems with an arbitrarily large constant pointwise delay in the inputs, we propose a new construction of exponentially stabilizing sampled control laws. Stability is achieved under an assumption on the size of the largest sampling interval. The proposed design is based on an adaptation of the two main results of the reduction model approach. The stability of the closed loop systems is proved through a Lyapunov functional of a new type. [ABSTRACT FROM PUBLISHER]

The paper deals with sampled-data stabilization of delayed input-affine dynamics. To remove the infinite dimensionality, the design is set in the sampled-data context and the delay is compensated with a discrete-time predictor. A simulated example illustrates the performances. [ABSTRACT FROM PUBLISHER]

Starting from an optimal stabilizing controller designed for an input-affine continuous-time dynamics, the paper discusses the problem of computing a digital controller which preserves these properties under sampling. A direct digital approach which minimizes a modified cost functional is described. Some simulated examples illustrate the performances. [ABSTRACT FROM PUBLISHER]

The aim of this paper is to provide a basic software tool involved in the design and the computation of nonlinear digital control schemes. The complete software SimNLSys will include different modules associated with each control scheme, aimed with respective objectives such as stabilization, damping, output matching or optimality, to quote a few. The software module presented here also encompasses the goal of computing solutions to nonlinear ODE's describing input-affine dynamics. The underlying methodologies propose challenging nonlinear sampled-data control strategies described in terms of Lie series expansions and computable through formal series calculus. The goal is to reach a friendly graphical user interface, to promote the practical efficiency of such strategies. For this, SymNLSys is built using the symbolic Matlab toolbox and the resulting mathematical control law expressions can be implemented directly on experimental plants. The paper describes the used differential geometric methods and discusses the implementation and limitations of the symbolic and numerical algorithms. Also some results obtained via this software are provided. [ABSTRACT FROM PUBLISHER]