Closed-Loop Equilibrium Strategies for General Time-Inconsistent Optimal Control Problems

Team-optimal closed-loop Stackelberg strategies in hierarchical control problems

This paper is concerned with the derivation of closed-loop Stackelberg (CLS) solutions of a class of continuous-time two-player nonzero-sum differential games characterized by linear state dynamics and quadratic cost functionals. Explicit conditions are obtained for both the finite and infinite horizon problems under which the CLS solution is a representation of the optimal feedback solution of...

Time Optimal Closed - Loop Fuzzy - Control Strategy for Nonlinear Lunar Lander Mission

A General Theory of Markovian Time Inconsistent Stochastic Control Problems

We develop a theory for stochastic control problems which, in various ways, are time inconsistent in the sense that they do not admit a Bellman optimality principle. We attach these problems by viewing them within a game theoretic framework, and we look for Nash subgame perfect equilibrium points. For a general controlled Markov process and a fairly general objective functional we derive an ext...

A New Optimal Solution Concept for Fuzzy Optimal Control Problems

In this paper, we propose the new concept of optimal solution for fuzzy variational problems based on the possibility and necessity measures. Inspired by the well–known embedding theorem, we can transform the fuzzy variational problem into a bi–objective variational problem. Then the optimal solutions of fuzzy variational problem can be obtained by solving its corresponding biobjective variatio...

Optimal Control for More General Problems

Optimal control is concerned with achieving a desired outcome, not by manipulating the path that can be taken within a specific system, but by manipulating the forces, or controls, that are fundamental to the system. It has no doubt been shown in the previous paper in this SSP series that optimal control problems are expressed using the functional, J, which serves as the performance index, in t...