LQR Optimal Control Method Based on Two-Degree-of Freedom Manipulator

The robotic arm is a very complex multi-input, multi-output nonlinear system, and it needs to have high trajectory tracking accuracy. In this paper, a mathematical modeling and optimal trajectory tracking control of a two-axis robotic arm is adopted to address the problem of unstable and large input control of the robotic arm. Firstly, the dynamic characteristics of the robot arm are analyzed, and then the dynamic model of the robot arm is established by Lagrange's equation method. Secondly, the control model of the system is derived, and the linear quadratic optimal control is introduced, and the weight matrices R and Q in the quadratic performance index function are optimized by genetic algorithm. The experimental results through simulation show that the optimized control method can effectively improve the convergence speed and stability of the system and obtain a better trajectory tracking effect compared with the traditional empirical values, which verifies the feasibility of the method.