MOTION CONTROL OF PHOTOVOLTAIC MODULE DUST CLEANING ROBOTIC ARM BASED ON MODEL PREDICTIVE CONTROL

Carbon neutralization has become a global consensus for green development, and solar photovoltaic power generation has become one of the key technologies for carbon reduction. The presence of dust on a photovoltaic module affects power generation, so the trajectory tracking control of dust removal robotic arm for photovoltaic modules is of great significance for improving power generation efficiency. In this study, a composite trajectory tracking strategy based on model predictive control is designed to track the desired angle of each joint, which is the control objective for the trajectory tracking of the photovoltaic module's dust cleaning robotic arm. The control strategy consists of a model predictive controller and a disturbance observer. Firstly, when there is no external disturbance acting on the system, and the robotic arm model is accurate, the trajectory tracking prediction optimization problem is constructed, and an error feedback correction mechanism is introduced so that the dust cleaning robotic arm tracks the desired trajectory asymptotically. Secondly, when there are model parameter deviations, system time variation, external disturbances, or other uncertain factors, a composite control strategy is established by combining the disturbance observer and model predictive control to compensate for the effects of disturbances through feedback, thus improving the stability and accuracy of the robotic arm control system. Finally, the feasibility of the composite control tracking strategy is verified by numerical simulation. The results show that the designed predictive controller has high error control accuracy and fast solution speed, and it can realize realtime and robust trajectory tracking of the robotic arm with a constrained dust cleaning assembly.