Название: Robot Control and Calibration: Innovative Control Schemes and Calibration Algorithms
Автор: Xin Luo, Zhibin Li, Long Jin, Shuai Li
Издательство: Springer
Серия: SpringerBriefs in Computer Science
Год: 2023
Страниц: 132
Язык: английский
Формат: pdf (true), epub
Размер: 29.1 MB
This book mainly shows readers how to calibrate and control robots. In this regard, it proposes three control schemes: an error-summation enhanced Newton algorithm for model predictive control; recurrent neural network (RNN) for solving perturbed time-varying underdetermined linear systems; and a new joint-drift-free scheme aided with projected ZNN, which can effectively improve robot control accuracy. Moreover, the book develops four advanced algorithms for robot calibration – Levenberg-Marquarelt with diversified regularizations; improved covariance matrix adaptive evolution strategy; quadratic interpolated beetle antennae search algorithm; and a novel variable step-size Levenberg-Marquardt algorithm – which can effectively enhance robot positioning accuracy. We develop some control and calibration schemes for enhancing the tracking and positioning accuracy of the robot. The first model is a Model Predictive Control (MPC) scheme for robot trajectory tracking, which can optimize tracking error, velocity norm, and acceleration norm. The second model is a new recurrent neural network (RNN), which has better performance in dealing with time-varying underdetermined linear systems with double limits. The third model is a novel Joint Drift Free (JDF) scheme synthesized by the Projection Zeroing Neural Network (PZNN) model, which can effectively solve the motion generation and control of redundant manipulators under disturbance.
