| Industry robot works in a structural environment and can free human being from the heavy, boring, repetition physical labor. Nowadays, robot has been widely used in the field of automobile, electronics, information production and so on. China as a big production country, industry robot has become its important part during the process to be a strong production country. Industry robot is a very complicated non-linear system, which has multiple input and output. It has the character of time-varying, strong couple and non-linear. The controller, which is used in robot nowadays, usually ignores the robot's dynamic effect. However, when robot runs in the high speed condition, its dynamics effect is very huge, which can't be ignored. At this time, the speed and payload of robot varies greatly. In order to improve robot's working accuracy, the controller's parameters, should change, too. Therefore, to solve the control problems when robot runs at a high speed under an unknown working trajectory and runs at a high speed under a known working trajectory, the paper make a deeply research. The research work has been supported by the national 863 important project. The project number is 2009AA043901.To the transport robot whose payload is 10kg, the kinematics, static and dynamics analysis of the robot are performed in this paper. Different from the traditional single joint modeling, the paper proposed a new method to set up the multiple joints'transfer function. The dynamic function of robot can be simplified by some numerical solution obtained in the trajectory and the multiple joints'transfer functions can be set up, which takes the joints'dynamic effect into consideration.The paper proposed a new method to setup a joints'nonlinear PID controller and neural network, to solve the problem when robot run in a high speed condition whose working trajectory is known. To transport robot, the working trajectory is known means that the material's putting position is determined and can be obtained by teaching. The dynamic parameters of robot have been deeply researched when it runs under a high speed condition. Then the state parameters affecting the robot's dynamic effect can be obtained, which is the robot's angular position vetorθ, the angular speed vectorθ? and the angular acceleration vectorθ?? .To the PID main controller of the robot platform in the project, the relationship between the dynamic parameters and the PID coefficients has been deeply researched.The tip of the robot is firstly manipulated running along a known trajectory in experiment. At the sample time, the robot's joints'angular position, the angular velocity and the angular acceleration can be obtained by the photoelectric encoder. The PID parameters at the sampling point can be attained, too. The joints'angular positionθis firstly chosen to be the controller's state parameter. Then the nonlinear expression between the robot's PID parameters and the joints'angular position can be inferred by the least square method. So the robot's joints'nonlinear PID controllers can be set up.Moreover, the robot joints'angular speed vectorθ? and the angular acceleration vectorθ?? , which may affect the PID controllers, have been taken into consideration. The neural network intelligent modeling technology is used to setup the BP neural model between the robot's joints'angular position vectorθ, angular speed vectorθ?, angular accelerationθ?? the PID parameters k p, k i, k d.The paper has designed the improving immune clone select and DNA controllers to deal with the problem when the transport robot working in a high speed motion condition whose trajectory is unknown. To the transport robot, the working trajectory is unknown means that robot fetches the scattering material in high speed and the trajectory can be detected in real-time by some sensors, such as the visual sensor and so on. Due to the unknown working trajectory means that the robot joints'angular position, angular velocity and angular acceleration can only obtained in real time. The high accuracy and high speed goal request the main controller's parameters should optimistic at any time. Due to this characteristic, the paper proposed a control scheme which is the robot joints'model's real-time recognition and the controller's parameters'real-time self tuning.Based on the joints'transfer functions set up, the model of the robot's joints can be identified by the weighted type least square method. The working mechanism of the DNA compute and immune algorithm has been deeply researched and improve partly. Then the improving immune clone select and improving DNA algorithm have been creatively designed and used to tune the controllers'parameters in real time. The control scheme can restrain the effect of various uncertain factors'disturb and can make sure the control parameter's optimality at any time, which has some adaptability and intelligence. This control scheme can be used in the condition that the moving trajectory is time-varying which is recognized by the robot itself in real time, and the demand of accuracy and speed is very high.In the end of the paper, several simulation experiments have been caught out to test the researched intelligent control algorithm. All of the algorithm are coded by the Visual C# program language and embedded into the control system. Then some motion control experiments are performed. The final experiment results show that, the new method is better than the traditional single PID control in the aspect of speed and accuracy. The running time of nonlinear PID control and the neural network model is 1.8ms and 3ms. The final tracking error of the algorithm is±0.28mm and±0.1mm. The neural network model has a stronger real-timing character, which can be used to several robots requiring running in a high speed condition when working trajectory is regular and can be known by teaching.The running time of improving Immune clone selection algorithm and DNA compute is 72ms and 50ms, and the final tracking error is±0.08mm and±0.06mm. The improving DNA compute need less running time and can reached a higher tracking accuracy than that of the immune clone select algorithm, which is suitable for high speed motion command when working trajectory is varying and be recognized by the robot itselfThe creative achievements can be shown as following:1. In the aspect of robot joints'modeling, different from the traditional modeling manner, the robot's multiple joints transfer functions have been inferred, which take the robot joints'coupling effect into consideration.2. The dynamic expression has been deeply analyzed, and the state parameters affecting the robot's dynamic effect are obtained, which are the robot's joint angular position vectorθ, the angular velocity vectorθ? and the angular acceleration vectorθ?? .3. To the robot platform's main PID controllers, the relationship between the robot dynamic state parameters and the controllers'coefficients in qualitative and quantitative analysis.4. The improving immune select clone algorithm and DNA computing algorithm.The research achievement can solve the problem of the high accuracy requirement when robot run in a high speed motion condition, promote the automation in mechanic industry and boost the social productivity.
|
PDF Full Text Request