Design And Implementation Of Control System Of Solar Panel Cleaning Robot Based On Crystal Silicon

The global fossil fuel reserves are depleting rapidly,leading to a shift towards diversified energy sources.Solar power has emerged as a popular alternative,with an increasing number of solar power plants being set up and a rise in the share of solar power in total energy generation.Silicon-based cells are commonly used in solar panels due to their high power generation efficiency,low manufacturing costs,and mature technology.However,it is crucial to maintain solar power plants to ensure optimal performance.The accumulation of dust on the surface of solar panels over long periods can significantly reduce power generation efficiency.Regular cleaning of solar panels is essential to improve power generation efficiency and extend their service life.This paper presents the design and implementation of an autonomous cleaning robot for crystalline silicon-based solar panels.The robot is equipped with a sophisticated hardware system and a highly reliable control system,which allow it to efficiently and effectively clean the panels without human intervention.The first step of this study is to analyze the design requirements,and to develop the mechanical structure of the solar panel cleaning robot,The autonomous navigation and tracking of the robot cleaning are mainly discussed to ensure that the robot can clean the panels in all directions.After the completion of the design and selection,Aiming at the attitude problem of robot autonomous navigation,which is mainly discussed in this paper,the attitude solving methods in strapdown inertial navigation system are compared.The differences between these methods are carefully examined,the equivalent rotation vector method is used to update the attitude,and the coning error and paddling error generated during the robot movement are compensated by the twosample algorithm.Through experimental verification,the equivalent rotation vector method is obviously superior to other attitude solving algorithms,which can effectively suppress non-commutative error and greatly improve the accuracy of the data.Then,the speed of the dead-end navigation system is deduced by the attitude matrix of the strapdown inertial navigation system,and the data of the system is fused with that of the strapdown inertial navigation system.The speed difference between the two systems is passed into the Kalman filter as the observed value for processing.The attitude data is corrected by error estimation,and the navigation information with higher accuracy is output.The control system is designed with both hardware and software components.The hardware circuit is composed of several modules,including the main controller circuit,motor drive module circuit,attitude detection module circuit,wireless communication module circuit,and power supply circuit.Each module circuit is designed and a hardware development board is created.On the software side,the main program and sub-programs of each module are designed.Specific programs include a PID-based motor speed control program,a motor fault current detection program,an attitude adjustment control program,a driving map update program,a wireless communication program based on MQTT protocol,and an upper computer program.After designing the control system,the key modules of the robot are debugged.The voltage of each power supply in the circuit is measured by a multimeter,and the software part is debugged after confirming that the circuit is error-free.By fine-tuning the parameters of the PID algorithm,the motor motion parameters suitable for the design of this paper are selected.On this basis,the posture control program and the wireless communication program are programmed to verify the stability of each program.The overall experimental debugging of the robot is carried out by building an experimental platform,placing the cleaning robot on it,planning the route,and turning on the cleaning through the wireless communication module.The PID algorithm and the navigation algorithm are used to follow the trajectory of the robot and achieve allround cleaning of the battery panel.The results demonstrate that the combined navigation system has higher positioning accuracy than the Jetlink inertial guidance system during the process of sweeping the panels.