Minimum Energy Consumption Trajectory Optimization And Control Of High Speed And Heavy Duty Palletizing Robot

With the development of social productive forces, higher handling efficiency are demanded in the material handling areas as well as higher loading capacity for handling machine, so the palletizing robots with high load capacity and high speed have been more and more widely used for material handling. However, with the increase of load capacity and speed, the traditional control methods are difficult to meet the requirement of high positioning accuracy, and the traditional methods of trajectory planning also bring the problem of high-energy consumption. These problems put forward new challenges to the trajectory planning and motion control of palletizing robot with high load capacity and high speed.According to these requirements, this thesis focuses on the trajectory planning and motion control of optimal energy consumption for a palletizing robot with high load capacity and high speed. A new trajectory-planning algorithm of optimal energy consumption is proposed in this thesis, as well as a new fuzzy sliding mode variable structure control method for high precision motion control, and their effectiveness was validated by using an experimental system with an EtherCAT motion control system and a BS 130 palletizing robot.Firstly, the kinematic model and the dynamic model of palletizing robot are presented as the basis of this thesis. The forward and inverse kinematics are built by using the geometric method, and then its Jacobian matrix is obtained. The solid dynamic model is also built by using the second kind Lagrange’s equation, and then the coupled dynamic model is obtained by considering the joint flexibility. Furthermore, the virtual prototype model of the robot is established by using ADAMS, and the simulation is carried out for the validation of the kinematic and dynamic models.Secondly, considering minimizing energy consumption, the problem turns into how to optimize the trajectory without reducing the speed, plus appropriate moment and the whole story point constraint. Obtain energy optimal trajectory by using Fourth Order R-K method and multiple shooting method for the numerical solution of the problem, then make comparison with the traditional seven polynomial planning simulation’s result. Based on the method of optimized trajectory planning and according to the actual palletizing robot characteristics, make optimizing choosing of starting points, find out these points leading to lowest energy consumption, then analyze the relationships between their position and the system’s energy consumption.Thirdly, according to the robot system strong coupling, time-varying characteristics and uncertainty, combined with the advantages of fuzzy control and sliding mode control, a new controlling system is came up with. Wherein the sliding mode controller output control quantity, fuzzy control to control amount is corrected using the estimated state feedback in the form of the end position, and finally introduced to reduce friction compensation rapid joint friction on the robot start and stop performance.Finally, an experiment platform is built based on EtherCAT fieldbus, then friction identification and controlling performance test is performed on the robot. Friction identification test leads to a more precise joint friction model. Controlling performance test shows that repeated positioning accuracy could reach ±0.154 mm level and trajectory accuracy could reach ±0.16 mm level. This result is close to the advanced foreign palletizing robot. Thus, the effectiveness of this algorithm is verified. Besides, under best energy consumption trajectory, compared with seven polynomial trajectory, the real energy consumption is reduced by 15.308%, this also give evidence to the effectiveness of the optimal energy trajectory planning method. The work done here provides support for subsequent palletizing robot research.