A5063547339- Iterative Learning Control Systems
- Adaptive Control of Nonlinear Systems
- Piezoelectric Actuators and Control
- Control and Dynamics of Mobile Robots
University of Science and Technology Beijing
2020-2021
With the more extensive application of flexible robots, expectation for manipulators is also increasing rapidly. However, fast convergence will cause increase vibration amplitude to some extent, and it difficult obtain suppression satisfactory transient performance at same time. In order deal with problem, a fixed-time learning control method proposed realize convergence. The constraint on system outputs, uncertainty, input saturation addressed under framework. A novel adaptive law neural...
For the trajectory tracking and vibration suppression of a two-link flexible robot, neural networksbased fixed-time control method is proposed, which takes into account system uncertainty, output constraint input saturation. Novel adaptive law virtual are designed for solution uncertainty in convergence settings. The barrier Lyapunov function (BLF) used to solve problem system. Furthermore, chattering discussed detail. In end, through simulation, we present performance proposed method.