Abstract: An autonomously or semi-autonomously performed method of orchestration in a process control system (PCS) is provided, including performing tasks for monitoring an industrial system, including the PCS, each of the tasks being performed using inputs related to functionality of controller(s) of the PCS, the controller(s) having at least one control function related to a physical aspect of the PCS. For each of the tasks performed, dynamic state(s) of the PCS and the PCS's controller(s) are analyzed using machine learning (ML) algorithm(s), the dynamic state(s) being affected by the inputs. The method further includes performing, causing to be performed, or advising performance of an action responsive to an output of the ML algorithm(s), the action adjusting at least one of functionality of the controller(s) and functionality of or a setting used by or affecting a component of the PCS that affects the controller(s).