Cascaded Evolutionary Multi-Objective System Optimization for a Proportional Directional Control Valve

During the development of mechatronic systems hard- and software components are integrated into a single system. Mostly, a digital control concept is designed to control the interactions of the different sub-systems from different domains and to reach the desired system performance requirements. In the case of a proportional directional control valve, the closed-loop control response is used as a metric of the system performance. The performance can be either improved by optimizing the controller as well as the valve's hardware design parameters. When performing a holistic model-based system optimization, the optimization vector contains the controller and the hardware design parameters. A variation of the design parameters requires a time-consuming Finite-Element-Method (FEM) simulation. In contrast, the impact of different controller parameters on the system performance can be simulated with a low computational effort. Actually, following the control theory, the controller parameters must only be adjusted when the plant changes its characteristic. This contribution presents a cascaded evolutionary multi-objective optimization process which enables the subordinated controller design in the context of a holistic multi-objective system optimization of a directional control valve. The required optimization time decreases significantly since the outer optimization loop mainly focuses on the hardware improvement without the impact of the controller robustness. A real industrial application motivates the developed approach, but the cascaded process is evaluated more generally investigating well-known benchmark functions from the literature for multi-objective optimization.