An industrial control valve has been designed by Eaton (AxisPro® valve). The servo performance valve has onboard electronics that features external and internal sensor interfaces, advanced control modes and network capability. Advanced control modes are implement in the valves firmware. With the help of the white space it is possilbe to execute custom code directly on the valve that interact with these controls. Small OEM applications, like rubber moulding machines, benefit from the comination of build in controls and custom code, to provide adaptations for their special machines.

Inverse, multidimensional input-output flow mapping is very important for use of valves in precision motion control applications. Due to the highly nonlinear characteristic and uncertain model structure of the cartridge valves, it is hard to formulate the modelling of their flow mappings into simple parameter estimation problems. This contribution conducts a comprehensive analysis and validation of three- and four-dimensional input-output-mapping approaches for a proportional pilot operated seat valves. Therefore, a virtual and a physical test-rig setup are utilized for initial measurement, implementation and assessment. After modeling and validating the valve under consideration, as a function of flow, pressure and temperature different mapping methods are investigated. More specifically, state of the art approaches, deep-learning methods and a newly developed approach (extPoly) are examined. Especially ANNs and Polynomials show reasonable approximation results even for more than two inputs. However, the results are strongly dependent on the structure and distribution of the input data points. Besides identification effort, the invertibility was investigated.