Nonlinear Receding-Horizon Control of Rigid Link Robot Manipulators

TL;DR

This paper presents a nonlinear receding-horizon control method for rigid link robot manipulators that guarantees asymptotic tracking without online optimization, incorporating robustness enhancements through integral action and velocity estimation.

Contribution

It introduces a nonlinear predictive control law that avoids online optimization and guarantees tracking, with added robustness via integral action and a nonlinear observer.

Findings

Achieves asymptotic position tracking using only link position measurements.

Demonstrates robustness to payload uncertainties and viscous friction.

Validated through simulations on a two-link robot.

Abstract

The approximate nonlinear receding-horizon control law is used to treat the trajectory tracking control problem of rigid link robot manipulators. The derived nonlinear predictive law uses a quadratic performance index of the predicted tracking error and the predicted control effort. A key feature of this control law is that, for their implementation, there is no need to perform an online optimization, and asymptotic tracking of smooth reference trajectories is guaranteed. It is shown that this controller achieves the positions tracking objectives via link position measurements. The stability convergence of the output tracking error to the origin is proved. To enhance the robustness of the closed loop system with respect to payload uncertainties and viscous friction, an integral action is introduced in the loop. A nonlinear observer is used to estimate velocity. Simulation results for a two-link rigid robot are performed to validate the performance of the proposed controller. Keywords: receding-horizon control, nonlinear observer, robot manipulators, integral action, robustness.