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In order to improve the control performance, work quality, and reduce energy consumption of the hay cutter cutting operation, an objective function was established based on linear predictive control and combined with the characteristics of the hay cutter cutting operation. The sampling period was derived from the cutting kinematic error model to solve the control robustness, and the control time domain and prediction time domain were derived from the cutting dynamics model to improve control responsiveness. A load controller for the hay cutter cutting roller was designed. Simulink simulation showed that when the prediction parameter group (sampling period, prediction time domain, control time domain) selected through calculation and regression optimization was 0.8s, 15s, and 2s, the control accuracy and robustness were the best, the operation ability was the highest, the response speed to disturbances was the fastest, the suppression ability was the strongest, and the energy consumption was the lowest (9.27×106J). The on-site test results showed that the optimized predictive parameter group model cont-roller can effectively track and control the cutting load of the hay cutter, and the product quality met the standard requirements. At the same time, it improved the operation capacity of the hay cutter, making the system control response faster, production efficiency higher, and unit operation energy consumption smaller (1.382×107J). The method for establishing the parameter model of this controller provided a reference for the design of the control system of a generic forage crop harvester.