A systematic design approach of an embedded-control material-strength testing system

Abstract

In this paper, an embedded control system is developed to measure the yield strength of the material plate with an applied load. A systematic approach is proposed to handle special requirements of embedded control systems, which are different from computer-based control systems, as there are much less hardware resources and computational power available. An efficient control algorithm has to be designed to remove the CPU burden so that the microcontroller has enough power available. A three-step approach is proposed to address the embedded control issue: firstly, the mathematical description of the whole system is studied using both theoretical and experimental methods. A mathematical model is derived from the physical models of each component used, and an experiment is retrieved by employing Levy's method and least-square estimation to identify specific parameters of the system model. Secondly, a feedforward plus feedback controller is designed and simulated as a preparation for the embedded system implementation. The cerebellar model articulation controller (CMAC) is chosen as the feedforward part, and a PD controller is used as the feedback part to train the CMAC. Finally, the proposed algorithm is applied in the embedded system, and experiments are conducted to verify both the identified model and designed controller.

Neuro-fuzzy iterative learning control for 4-poster test rig

“…Yao et al (2013) and Yao et al (2017) established control methods to cancel acceleration harmonics that occur based on hydraulic nonlinearities. Chen et al (2017) offer a cerebellar model articulation controller for material strength testing to reduce the nonlinearity effect of the system.…”