A general model of decentralized stochastic control problem in which multiple controllers share part of their information with each other is investigated. The general model subsumes several models of information sharing in decentralized stochastic control as special cases. Structural results for optimal control strategies for the general model are presented. A dynamic program for finding the op...

The objective of this work is to explicitly point out the compromises in the identification and control stages in an acoustic noise suppression experiment, in terms of performance vs. controller order. The identification is a control–oriented robust procedure which takes into account both, parametric and non–parametric models, and is applied to the primary and secondary circuits of an acoustic ...

This paper deals with an iterative learning control law for multivariable systems. The desired inputs are supposed to be known and periodic. The principle of the control is to make outputs as close as possible to desired inputs at each new period. After the design of multivariable repetitive controller, we give the stability condition of the algorithm and some simulation results.

The adaptive robust control (ARC) for DC motors subjected to parametric uncertainties, disturbances and input saturation is considered in this study. To achieve high performance while keeping the control authority within saturation limit, a saturated ARC scheme is proposed. In this scheme, a variable-gain saturation function is introduced for the virtual control law, so that the amplitude of th...

Optimal control theory is applied to a system of ordinary differential equations modeling a two-strain tuberculosis model. Seeking to reduce the latent and infectious groups with the resistant-strain tuberculosis, we use controls representing two types of treatments. The optimal controls are characterized in terms of the optimality system, which is solved numerically for several scenarios.

In this paper we generalize a one-dimensional optimal control problem with DNSS property to a two-dimensional optimal control problem. This is done by taking the direct product of the model with itself, i.e. we combine two similar system dynamics under a joint objective functional that is separable in both states and controls. This framework can be applied to the construction of various optimal...

We offer a new perspective on games of irreversible investment under uncertainty in continuous time. The basis is a particular approach to solve the involved stochastic optimal control problems which allows to establish existence and uniqueness of an oligopolistic open loop equilibrium in a very general framework without reliance on any Markovian property. It simultaneously induces quite natura...