Robotic Arm Servo Control Using Chaos Genetics and Fuzzy Decision Making
The robot arm has poor adaptive ability in complex industrial environment and cannot make corresponding adjust-ments.In order to improve the position control accuracy of the robot arm,chaotic genetics and fuzzy decision-making are applied to the position servo control.Taking the WY700-1 manipulator as an example,the dynamic diagram of the manipulator is given.For each link of the manipulator,the coordinate system is established by the Denavit-Hartenberg coordinate transformation meth-od,and the homogeneous transformation matrix is used to describe the relationship between two consecutive joints.The dynamic model of the end effector of the manipulator is constructed by combining the motion of each joint.According to the proportional-in-tegral-derivative control theory,the position servo control model is constructed,and the relevant parameters such as proportional-integral-derivative are specified by the fuzzy decision-making model,and the ant colony algorithm and the chaos theory are inte-grated to design the chaotic ant colony algorithm.By searching the variable space to be optimized,get the best control coefficient parameters,and complete the position servo control of the manipulator.In the simulation test stage,the servo control effect of the manipulator is verified from different running trajectories such as straight lines,curves,and arcs.The test results show that the pro-posed method has superior control accuracy,can effectively suppress error interference,and can meet basic accuracy requirements.
Mechanical ArmAnt ColonyLocationServo ControlChaotic VariableProportional Integral Deri-vative Controller
NETL
NSTL
万方数据
维普
