Improving Robustness of Computed-Torque Schemes via LMI-Based Nonlinear Feedback
- Resource Type
- Conference
- Authors
- Alonso Diaz, Jesus; Ibarra, Jorge; Bernal, Miguel
- Source
- 2020 17th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE) Electrical Engineering, Computing Science and Automatic Control (CCE), 2020 17th International Conference on. :1-6 Nov, 2020
- Subject
- Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Computational modeling
Robustness
Trajectory tracking
Linear matrix inequalities
Analytical models
Trajectory
Torque
Computed-Torque Control
Tracking
Parallel Distributed Compensation
Linear Matrix Inequality
- Language
- ISSN
- 2642-3766
This paper is concerned with a novel computed-torque technique for trajectory tracking, which enhances robustness by replacing some of the system nonlinearities in the inner-loop feedback by the signals of the desired trajectory. This substitution leads to a nonlinear error system whose stabilization is achieved via a nonlinear outer-loop feedback in the form of parallel distributed compensation, whose gains are solved in terms of linear matrix inequalities derived from the direct Lyapunov method and exact convex modelling of nonlinearities. The proposal makes use of a recently appeared factorization which explicitly allows extracting the error signal in the difference of identical expressions that depend on a different set of variables. Simulations suggest that the magnitude of the computed-torque signal can be significantly reduced when compared with ordinary schemes while augmenting robustness by employing user-generated signals instead of measurements where appropriate.