A canonical optimal control problem for linear systems with timevarying coefficients is considered in the class of discrete controls. On the basis of linear programming methods, two primal and two dual methods of constructing optimal open-loop controls are proposed. A method of synthesis of optimal feedback control is described. Results are illustrated by a fourth-order problem; estimates of ef...

An optimal control problem with linear dynamics and convex but not necessarily quadratic and possibly infinite-valued or nonsmooth costs can be analyzed in an appropriately formulated duality framework. The paper presents key elements of such a framework, including a construction of a dual optimal control problem, optimality conditions in open loop and feedback forms, and a relationship between...

The problem of controlling a perturbed open loop system so as to keep its performance errors within bounds is considered. The objective is to maximize the time during which performance errors remain below a prescribed ceiling, while the controlled system’s parameters are within a specified neighborhood of their nominal values. It is shown that there is an optimal open-loop controller that achie...

This contribution concerns the development of generic methods and tools for robust optimal control of high-pressure liquid chromatographic separation processes. The proposed methodology exploits a deterministic robust formulation, that employs a linearization of the uncertainty set, based on Lyapunov differential equations to generate optimal elution trajectories in the presence of uncertainty....

this paper introduces a technique for controlling a class of uncertain chaotic systems using an adaptive fuzzy proportional-integrator-derivative (pid) controller with h∞ tracking performance. the purpose of this work is to achieve optimal tracking performance of the controller using backtracking search algorithm (bsa). bsa, which is a novel heuristic algorithm, has an easy structure with singl...

In this paper we examine the application of evolutionary algorithms to find open-loop control solutions of the optimal control problem arising from the semidiscretisation of a linear parabolic tracking problem with boundary control. The solution is compared with the solutions obtained by methods based upon the variational equations of the Minimum Principle and the finite element method.

We consider the problem of planning under observation and motion uncertainty for nonlinear robotics systems. Determining the optimal solution to this problem, generally formulated as a Partially Observed Markov Decision Process (POMDP), is computationally intractable. We propose a Trajectory-optimized Linear Quadratic Gaussian (T-LQG) approach that leads to quantifiably near-optimal solutions f...

This paper is concerned with a stochastic linear-quadratic optimal control problem in finite time horizon, where the coefficients of system are allowed to be random, and weighting matrices cost functional random indefinite. It shown, Hilbert space approach, that for existence an open-loop control, convexity (with respect control) necessary; uniform convexity, which slightly stronger, turns out ...

Closed-loop control relies on sensory feedback that is usually assumed to be free . But if sensing incurs a cost, it may be costeffective to take sequences of actions in open-loop mode. We describe a reinforcement learning algorithm that learns to combine open-loop and closed-loop control when sensing incurs a cost. Although we assume reliable sensors, use of open-loop control means that action...