We consider stability analysis and state feedback synthesis for Linear Parameter Varying (LPV) systems. LPV systems are de"ned as linear systems whose dynamics depend on exogenous time-varying parameters. Stability analysis of LPV systems involves testing the stability of a family of possible parameter trajectories. Similarly, stabilization and optimal control of LPV systems involves constructi...

This paper presents a sequential optimization technique for the design of optimal trajectories while minimizing a cost index subject to system dynamics, path and actuation constraints. A novel coordinate transformation is introduced to cast the non-convex trajectory generation problem as a convex optimization problem. A sequential linear programming approach is discussed to solve the resulting ...

UAV trajectory planning is often done in a two-step approach, where low-dimensional path refined to dynamic trajectory. The resulting trajectories are only locally optimal, however. On the other hand, direct higher-dimensional state spaces generates globally optimal solutions but time-consuming and thus infeasible for time-constrained applications. To address this issue, we propose $$\delta $$ ...

This paper presents a decentralized, model predictive control algorithm for the reconfiguration of swarms of spacecraft composed of hundreds to thousands of agents with limited capabilities. In our prior work, sequential convex programming has been used to determine collision-free, fuel-efficient trajectories for the reconfiguration of spacecraft swarms. This paper uses a model predictive contr...

In this paper we consider the minimum time population transfer problem for the z-component of the spin of a (spin 1/2) particle driven by a magnetic field, controlled along the x axis, with bounded amplitude. On the Bloch sphere (i.e. after a suitable Hopf projection), this problem can be attacked with techniques of optimal syntheses on 2-D manifolds. Let (−E,E) be the two energy levels, and |Ω...

We consider the continuous trajectories of the vector field induced by the primal affine scaling algorithm as applied to linear programming problems in standard form. By characterizing these trajectories as solutions of certain parametrized logarithmic barrier families of problems, we show that these trajectories tend to an optimal solution which in general depends on the starting point. By con...

In recent papers it has been suggested that human locomotion may be modeled as an inverse optimal control problem. In this paradigm, the trajectories are assumed to be solutions of an optimal control problem that has to be determined. We discuss the modeling of both the dynamical system and the cost to be minimized, and we analyze the corresponding optimal synthesis. The main results describe t...

Necessary conditions of optimality, in the form of a maximum principle, are derived for a class of optimal control problems, certain of whose controls are represented by measures and whose state trajectories are functions of bounded variation. State trajectories are interpreted as robust solutions of the dynamic equations, a concept of solutions which takes account of the interaction between th...

The application of neural networks technology to dynamic system control has been constrained by the non-dynamic nature of popular network architectures. Many of difficulties are-large network sizes (i.e. curse of dimensionality), long training times, etc. These problems can be overcome with dynamic neural networks (DNN). In this study, intelligent optimal control problem is considered as a nonl...

The problem of determining minimum-fuel maneuver sequences for a four-spacecraft formation is considered. The objective of this paper is to find fuel-optimal spacecraft trajectories that transfer four spacecraft from an initial parking orbit to a desired terminal reference orbit while satisfying a set of constraints on the formation at the terminal time. Trajectories involving both one and two ...