Improved fuzzy neural network control for the clamping force of Camellia fruit picking manipulator

During the operation of vibrating mechanism, push-shaking camellia fruit picking manipulator needs to ensure a constant force output clamping hydraulic motor in order make sure that tree trunk wouldn't loosen or damage, which may affect its later growth, during process. In this regard, paper derived state space model valve-controlled system manipulator, and fuzzy wavelet neural network (FWNN) was designed on basis traditional incremental PID control principle parameters were optimized by improved grey wolf optimizer (GWO). And then, simulated with MATLAB/Simulink software without external interference, compared analyzed it controller (FPID) controller. The results show FPID have slow response poor robustness, while (IFWNN PID) possesses characteristics fast strong can well meet requirement motors. Finally, field test carried out manipulator. controlled IFWNN shortens time 20.0% reduces damage 13.6% controller, is verified requirements machine.