Statistical learning for probability-constrained stochastic optimal control

Mixed Strategy for Constrained Stochastic Optimal Control

Choosing control inputs randomly can result in a reduced expected cost in optimal control problems with stochastic constraints, such as stochastic model predictive control (SMPC). We consider a controller with initial randomization, meaning that the controller randomly chooses from K+1 control sequences at the beginning (called K-randimization). It is known that, for a finite-state, finite-acti...

Optimal probability density function control for NARMAX stochastic systems

This paper presents a new control strategy for a class of non-Gaussian stochastic systems so that the output probability density function (PDF) of the system can be made to follow a desired PDF. The system considered is represented by an Nonlinear AutoRegressive and Moving Average with eXogenous (NARMAX) inputs with input channel time-delay and non-Gaussian noise. Amulti-step-ahead nonlinear cu...

Quantitative Determination Of Optimal Fiscal And Monetary Policies: A Stochastic Optimal Control Analysis For Iran

Two approaches to constrained stochastic optimal control problems

In this article, we study and compare two approaches to solving stochastic optimal control problems with an expectation constraint on the final state. The case of a probability constraint is included in this framework. The first approach is based on a dynamic programming principle and the second one uses Lagrange relaxation. These approaches can be used for continuous-time problems; we provide ...

State-Constrained Stochastic Optimal Control Problems via Reachability Approach

This paper deals with a class of stochastic optimal control problems (SOCP) in presence of state-constraints. It is well-known that for such problems the value function is, in general, discontinuous and its characterization by a Hamilton-Jacobi equation requires additional assumptions involving an interplay between the boundary of the set of constraints and the dynamics of the controlled system...