The convexity of return functions in dynamic programming implies the possibility of employing standard procedures of convex programming for the searches of minima of functions which are performed at every stage of the computational procedure. In the present work by means of a geometric approach are derived necessary and sufficient conditions for the convexity of return functions in dynamic optimization problems with bounded states and controls and in presence of isoperimetric constraints.
The purpose of this paper is to derive constructive necessary and sufficient conditions for the problem of disturbance decoupling with algebraic output feedback. Necessary and sufficient conditions have also been derived for the same problem with internal stability. The same conditions have also been expressed by the use of invariant zeros. The main tool used is the dual- lattice structures introduced by Basile and Marro [R4].
In this paper the exact decoupling problem of signals that are accessible for measurement is investigated. Exploiting the tools and the procedures of the geometric approach, the structure of a feedforward compensator is derived that, cascaded to a linear dynamical system and taking the measurable signal as input, provides the control law that solves the decoupling problem and ensures the internal stability of the overall system.
The synthesis of a feedforward unit for optimal decoupling of measurable or previewed signals in discrete-time linear time-invariant systems is considered. It is shown that an optimal compensator can be achieved by connecting a finite impulse response (FIR) system and a stable dynamic unit. To derive the FIR system convolution profiles an easily implementable computational scheme based on pseudoinversion (possibly nested to avoid computational constraints) is proposed, while the dynamic unit...
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