Adaptive Control of Mechanical Manipulators

TLDR

Model‑based nonlinear control of mechanical manipulators can suppress disturbances and track trajectories uniformly, but its performance degrades with inaccurate dynamic models and requires careful handling of excitation and disturbance effects. This paper proposes a parameter‑adaptive control scheme that augments the nonlinear model‑based controller with adaptive laws. The scheme is specifically tailored to the nonlinear controller and has been proven stable in a fully nonlinear setting. After adaptation, joint error dynamics are decoupled with uniform disturbance rejection across all configurations, as demonstrated by simulations and experiments on an Adept One industrial robot.

Abstract

When an accurate dynamic model of a mechanical manipu lator is available, it may be used in a nonlinear, model-based scheme to control the manipulator. Such a control formula tion yields a controller that suppresses disturbances and tracks desired trajectories uniformly in all configurations of the manipulator. Use of a poor dynamic model with this kind of model-based decoupling and linearizing scheme, however, may result in performance that is inferior to a much simpler, fixed-gain scheme. In this paper, we develop a parameter-adaptive control scheme in a set of adaptive laws that can be added to the nonlinear, model-based controller. The scheme is unique be cause it is designed specifically for the nonlinear, model- based controller and has been proven stable in a full, nonlin ear setting. After adaptation, the error dynamics of the joints are decoupled with uniform disturbance rejection in all ma nipulator configurations. The issues of sufficient excitation and the effect of disturbances are also discussed. The theory is demonstrated with simulation results and also with data from an implementation for an industrial robot, the Adept One.