Stochastic optimal control is a branch of control theory that deals with uncertain system parameters. One of the requirements for an accurate description of systems is a complete knowledge of the structure or values of the basic parameters of the system, which if achieved, the optimization process will also have accurate results. In this paper, we highlight a method for optimizing control under the control of a stochastic uncertainty approach that involves the use and dependence on uncertain parameters for systems whether they are distributed by a distribution function or within other sets of potential values by using the python language. Finally, the numerical results were implemented in python using the GEKKO package.
No takes yet. Share an insight, caveat, or question.
Alridha et al. (2023) studied this question.