Design And Implementation Of Adaptive Control Algorithms For The Leveling Machine Attitude Control System

The leveling machine is a kind of engineering vehicle that can level the ground by horizontally moving the shovel at the front end of the machine.It has been widely used in the leveling system of agriculture and construction.Compared with the traditional method of manual leveling,the leveling machine is significantly improved with respect to efficiency and cost.At present,most of the domestic leveling machine controllers rely on importing,and the self-developed controllers have lower precision.Therefore,more and more researchers in China are engaged in research and development of leveling technology in recent years.Among various research directions,modeling of attitude regulation mechanism and selection of attitude control algorithms are two research highlights.However,the leveling machine involves electromechanical coupling and has properties of strong nonlinearity and complex dynamics.As a result,modeling methods commonly used in the past often include many system simplifications,and corresponding dynamic models cannot reflect actual dynamics.In addition,traditional control algorithms such as PID are often used in domestic leveling controllers.The control effects of these algorithms are often poor.In order to obtain higher leveling accuracy,it’s not only necessary to establish a system model which has more practical value,but also to design a better attitude control algorithm.In-depth research on these issues has been carried out in this paper.The main contents and results are as follows:(1)A control scheme for the leveling machine of a single laser transceiver is proposed,which can significantly reduce the cost.The control principle of the scheme is introduced.In order to facilitate the indoor control experiment,the experimental platform of the leveling machine attitude control system is designed and built.The feasibility of the H-bridge as the experimental platform driving circuit is verified by PWM output experiment.(2)The modeling principle of step response method is introduced.Combined with the properties of this system,the modeling method of using the step response of the angular velocity to obtain the transfer function after deriving the angle is designed to solve the problem that the step response of the angle is divergent.The modeling experiments of the rolling angle and pitch angle control mechanisms of the leveling machine were carried out respectively.Multiple sets of step responses were recorded under different working points and voltage step signals,and approximate second-order system parameter models were obtained.These models contribute to the analysis and design of the controller.(3)The attitude control algorithm of the pitch angle of the leveling machine based on fuzzy adaptive PID is designed.The appropriate membership function,fuzzy inference method and defuzzification method are selected.The fuzzy rule table suitable for the system is obtained by testing.The feasibility of the algorithm is verified by simulation.The C program was written and the attitude control experiment was carried out on the experimental platform.The results show that the control effort of the shovel is improved after using fuzzy adaptive PID.(4)The principle of minimum variance self-tuning control is introduced.An attitude control algorithm for the roll angle of the leveling machine based on the minimum variance self-tuning is designed.The control performance is verified by simulation and the robustness of minimum variance control is tested.Minimum variance control is implemented on the experiment platform.The results show that after using the minimum variance self-tuning control,the leveling accuracy and various performance indicators of the system are greatly improved compared with the PID control.