A numerical method is proposed for optimal robust control synthesis. The method applies to the case when the coefficients of the characteristic polynomial depend linearly on the uncertain parameters. A primal/dual pair of infinite-dimensional convex problems is solved by successive finite-dimensional approximations. The primal/dual pair has no duality gap, and both upper and lower bounds produc...

In this paper, the linear-quadratic-Gaussian (LQG) optimal control problem is considered and a robust minimax controller composed of the Kalman filter and the optimal regulator is synthesized to guarantee the asymptotic stability of the discrete time-delay systems under both parametric uncertainties and uncertain noise covariances. Designed procedures are finally elaborated with an illustrative...

A general approach to optimal motion synthesis of constrained multibody systems is presented. It applies to controlled mechanical systems such as industrial manipulators and legged-locomotion systems. An optimal control problem is stated. A parametric optimization technique based on approximating joint motion coordinates using spline functions of class C is developed to recast this primary prob...

This paper deals with a parametric multi-period integer-valued inventory model for perishable items. Each item in the stock perishes in a given period of time with some probability. Demands are assumed to be random. and the probability that an item perishes is not known with certainty. Expressions for various parameter estimates of the model are established and the. problem of finding an optima...

We present a numerical method for finite-horizon stochastic optimal control models. We derive a stochastic minimum principle (SMP) and then develop a numerical method based on the direct solution of the SMP. The method combines Monte Carlo pathwise simulation and non-parametric interpolation methods.Wepresent results froma standard linear quadratic controlmodel, and a realistic case study that ...

The problem of optimal feed-rate planning along a curved tool path for 3-axis CNC machines with a jerk limit for each axis is addressed. We prove that the optimal feed-rate planning must use “Bang-Bang” control, that is, at least one of the axes reaches its jerk bound throughout the motion. As a consequence, the optimal parametric velocity can be expressed as a piecewise analytic function of th...

A model predictive control algorithm was developed for regulating glycemia in subjects with type 1 diabetes mellitus using exogenous insulin infusion to reject disturbances from oral carbohydrate consumption. A clinically validated nonlinear physiological model of glucose metabolism was linearized and served as the basis for the controller. The control law was developed using multi-parametric p...

A dynamic state feedback control stmcture is proposed in this paper. The scheme is conceived as an adaptive controller with the equilibrium in an LgV control law as the uncertain parameter, which allows the implementation of the controller for systems with unknown equilibnum. A new property of LgV controllers is given, and it is proven that this and other important properties carry on to the pr...

This article develops a model for evaluating alternative hedging strategies for financially constrained firms. A key advantage of the model is the ability to capture the intertemporal effects of hedging on the firm’s financial situation. We characterize the optimal hedge. A wide range of alternative hedging strategies can be specified and the model allows us to determine in each case if the hed...

The aim of this work is to motivate the use of linear flatness, or controllability, to design a feedback control law for the rather challenging mechanism known as the ‘Furuta pendulum’. This is achieved by introducing three feedback controller design options for the stabilization and rest-to-rest trajectory tracking tasks: a direct pole placement approach, a hierarchical high-gain approach and ...