A Direct Probabilistic Optimization Method for Constrained Optimal Control Problem

A new stochastic algorithm called Probabilistic Global Search Johor (PGSJ) has recently been established for global optimization of nonconvex real valued problems on finite dimensional Euclidean space. In this paper we present convergence guarantee for this algorithm in probabilistic sense without imposing any more condition. Then, we jointly utilize this algorithm along with control
parameterization technique for the solution of constrained optimal control problem. The numerical simulations are also included to illustrate the efficiency and effectiveness of the PGSJ algorithm in the solution of control problems.

• Akbar Banitalebi
• Mohd Ismail Abd Aziz
• Rohanin Ahmad

• Optimal Control Problem
• Constraints
• Direct Methods
• Stochastic Algorithm

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