A hybrid offline-online neural predictor with gradient-descent optimization provides real-time nonlinear model predictive control for a 22-ton hydraulic excavator, improving tracking and flow efficiency over PID.
Modeling and velocity-field control of autonomous excavator with main control valve,
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Data-Driven Multi-step Nonlinear Model Predictive Control for Industrial Heavy Load Hydraulic Robot
A hybrid offline-online neural predictor with gradient-descent optimization provides real-time nonlinear model predictive control for a 22-ton hydraulic excavator, improving tracking and flow efficiency over PID.