Dynamic characterization and control of a parallel haptic interaction with an admittance type virtual environment

Abstract

Haptic interfaces, a kinesthetic link between a virtual environment and a human operator play a pivotal role in the reproduction of realistic haptic force feedback of the virtual reality-based simulators. Since most of the practical control theories are model-based, the identification of the robot’s dynamics, for precise modeling of the system dynamics, is a process of high significance and usage. This research addresses dynamic characterization, performance issues, and structural stability, associated with a parallel haptic device interaction with an admittance type virtual environment. In this regard, considering the Lion identification scheme, we characterized the dynamics of a robot nonlinearities in different operational points in the workspace, as a piecewise linear functions. Besides, utilizing the Lyapunov stability theory, we guaranteed the stability of the error dynamic of estimations. Next, by proposing a modified robust model predictive control scheme, one can guarantee the robust output feedback stability for a linear parametric variable system based on a quasi-min–max algorithm, subjected to the input constraints; besides, reducing the unwanted disturbances of the control efforts’ signals caused by switching in the piecewise linear dynamics. The simulations and the experimental implementation of a single-degree-of-freedom virtual-based haptic system are carried out. Results indicate that the identification is of high accuracy, and the appropriate convergence of parameters to the specific values are outlined. Besides, the output tracking error and its derivative behave desirably. The proposed method guarantees the robust stability of the system with output feedback subjected to input constraints. Uncertainties are well addressed in the prediction dynamics, thereby improving the output signals’ convergence to the desired output, being well suited for experimental practices of the haptic system.