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