We examine the complex problem of simultaneous position and internal force control in multiple cooperative manipulator systems. This is done in the presence of unwanted parametric and modeling uncertainties as well as external disturbances. A decentralized adaptive fuzzy controller scheme is proposed here. The controller makes use of a multi-input-multi-output fuzzy logic engine and a systematic online adaptation mechanism. Unlike conventional adaptive controllers, the proposed algorithm requires neither a precise mathematical model of the system's dynamics nor a linear parameterization of the system's uncertain physical parameters. Using a Lyapunov stability approach, the controller is proven to be robust in the face of varying intensity levels of the aforementioned uncertainties. The payload position/orientation error and that of the internal forces are also shown to asymptotically converge to zero under such conditions. The performance of the controller proposed is then compared with that of a well-known conventional adaptive controller.
['Wail Gueaieb', 'Fakhri Karray', 'Salah Al-Sharhan']
A robust adaptive fuzzy position/force control scheme for cooperative manipulators