The optimal sampling problem is the selection of instants together with control actions such that a given cost function minimized. In this article, we solve for free final time linear quadratic regulator. Each instant computed as minimization maximum eigenvalue formulated at each stage by previously applying dynamic programming. solution provides instants, actions, and in recursive constructive...

The linear quadratic regulator problem is central in optimal control and has been investigated since the very beginning of theory. Nevertheless, when it includes affine state constraints, remains challenging from classical “maximum principle” perspective. In this study we present how matrix-valued reproducing kernels allow for an alternative viewpoint. We show that objective paired with dynamic...

This work presents a control scheme to grid-connected single-phase photovoltaic (PV) system. The considered system has four 250 W solar panels, non-inverting buck-boost DC-DC converter, and DC-AC inverter with an inductor-capacitor-inductor (LCL) filter. aims track operate at the maximum power point (MPP) of PV regulate voltage DC link, supply grid unity factor. To achieve these goals, proposed...

During the last two decades, exoskeleton robot-assisted neurorehabilitation has received a lot of attention. The major reason for active research in rehabilitation is its ability to provide various types physical therapy at different stages and neurological recovery. performance greatly influenced by robot motion control system. Robot dynamics are nonlinear, but many linear schemes can adequate...

Stability properties of the problem of minimizing a (nonconvex) linear-quadratic function over an Euclidean ball, known as the trust-region subproblem, are studied in this paper. We investigate in detail the case where the linear part of the objective function is perturbed and obtain necessary and sufficient conditions for the upper/lower semicontinuity of the Karush-Kuhn-Tucker point set map a...

In this paper, an efficient computational approach is proposed to solve the discrete time nonlinear stochastic optimal control problem. For this purpose, a linear quadratic regulator model, which is a linear dynamical system with the quadratic criterion cost function, is employed. In our approach, the model-based optimal control problem is reformulated into the input-output equations. In this w...

A linear-like discrete-time fuzzy controller was designed to control and stabilize a single-pool irrigation canal. Saint Venant equations for open-channel flow were linearized using the Taylor series and a finite-difference approximation of the original nonlinear partial differential equations. Using the linear optimal control theory, a traditional linear quadratic regulator (LQR) was first dev...