Controllable Petri Net-Based Implementation Approach for Motor Control Systems

This paper presents a model-based implementation approach to realize a position servo control system for low-cost dc motors using a controllable Petri net (CrPN). The CrPN model inference engine is embedded inside the sensor node to form an autonomous agent, and the autonomous agent is further used to interpret and execute CrPN-based motor control models. The CrPN model can be evaluated to examine the properties of controllability and stability using reachability graphs before the model is deployed. The most important feature of the CrPN-based control approach is providing a feasible and low-cost solution without using any native code programming in microcontrollers. To evaluate the performance of our approach, proportional and proportional-integral position control schemes were both implemented using the CrPN approaches. The results from the Simulink simulations and the native code programming with C-language implementations were also provided for performance comparisons and validations.