| When two robot manipulators are transporting a common object, dual-arm force control is necessary to prevent excessive forces on the object. Typically, industrial manipulators do not provide a convenient control structure for development of dual-arm force control, and dynamic equation-of-motion (EOM) parameters are rarely known, which makes standard model-based force control difficult. To overcome these problems, a linear Model Reference Adaptive Control (MRAC) controller can be applied using an external computer, in which force measurements are used to provide trajectory updates that are transmitted from the MRAC controller to the existing industrial controller. The MRAC controller removes the requirement that the EOM be known, and the external computer provides the control structure for convenient dual-arm force control.; The Unimation PUMA 560 robot manipulator was used as the basis of this work, and a simulation environment was developed using MATLAB and Simulink. The simulation consisted of the dynamic equations-of-motion, a PID feedforward controller, inverse and forward kinematics, and a trajectory generator. Force was simulated as compliance, and used as the feedback signal for the external MRAC controller. These algorithms were all developed using published literature, and completely model an industrial manipulator and controller for position accuracy.; The MRAC algorithm was implemented as an adaptive compliance controller with force input and position output. Simulations show that this is an effective method for minimizing undesired forces during dual-arm transport of an object. Measured forces during transportation were reduced from 120 N without adaptive feedback, to less than 7 N with adaptive feedback, and moments were reduced from over 35 N-m without adaptive feedback to less than 7 N-m with adaptive feedback. |
