Design And Implementation Of SCARA Robot Drive And Control Integrated System Based On Hardware In The Loop

SCARA(Selective Compliance Assembly Robot Arm)robots usually apply a drivecontrol integrated system to achieve motion control.The mainstream drive-control integrated system uses a distributed multi-CPU architecture,and its data exchange rate is limited,which restricts the performance improvement and function expansion of the system.Therefore,this thesis designs and implements a drive-control integrated system based on a multi-core system on chip(So C).On the basis,algorithms such as parameter identification,feedforward control,and parameter self-tuning are used to improve system control performance.The thesis validates the system by using Hardware-in-the-loop(HIL)simulation technology to shorten the system confirmation period and improve development efficiency and security.This thesis analyzes the current research status of the drive-control integrated system,determines the characteristics of the system,uses software and hardware collaborative design methods to divide the system into modules,and completes the system architecture design and timing analysis.With the minimum dynamic parameter set and Stribeck friction model,the thesis linearizes the dynamic model and uses the least-squares method to realize parameter identification.For increasing the parameter identification accuracy,the thesis uses an improved Fourier series to optimize the excitation trajectory,which can avoid the sudden change in speed during the start and stop process leading to the robot jitter and enhance the anti-noise capability of the identification process.After obtaining the dynamic model,this thesis proposes a model-based feedforward control algorithm to achieve torque compensation,reducing the impact of the robot's nonlinear time-varying characteristics.At the same time,to simplify the parameter adjustment process and reduce the impact of the manual experiment on the control performance,this thesis uses the reinforcement learning algorithm with selflearning and decision-making ability to realize the auto-tuning of controller parameters.Finally,this thesis employs HIL technology to design and implement a joint test system based on the drive-control integrated system,which performs the system parameter identification and robot control performance test.Simulation and HIL experiment results show that the So C-based drive-control integrated system can meet the control requirements of SCARA robots.The parameter identification strategy proposed in this paper can obtain a highprecision dynamic model.Based on this model,feedforward control and parameter self-tuning technology can effectively improve the robot's motion performance.