The benefits of model predictive control (MPC) have been well established; however its application to reference tracking on digital servo drives (DSDs), which typically have very fast update rates, is limited by the computational power of present-day processors. This paper presents a novel MPC formulation, which provides a mechanism to trade-off online computation effort with tracking performance, while maintaining stability. This is achieved by introducing a trajectory horizon, which is distinct from the prediction and control horizons typically encountered in MPC formulations. It is shown that increasing the trajectory horizon inherently leads to improved tracking; however larger horizon lengths also have the unwanted effect of increasing online computation. The proposed MPC formulation is compatible with recently developed explicit MPC solutions, and hence the burden of online optimization is avoided. The new approach is successfully implemented on an industrial machine tool DSD, and in terms of tracking accuracy, is shown to outperform the incumbent approach of cascaded PID control.

In this paper we argue that the focus of much of the visual servoing literature has been on the kinematics of visual control and has ignored a number of fundamental and significant dynamic control issues. To this end the concept of visual dynamic control is introduced, which is concerned with dynamic effects due to the manipulator and machine vision sensor which limit the performance. These must be explicitly addressed in order to achieve high-performance control. The paper uses simulation and experiment to investigate the feedback control issues such as the choice of compensator, and the use of axis position, velocity or torque controlled inner-loops within the visual servo system. The limitations of visual feedback control lead to the investigation of target velocity feedforward control, which combined with axis velocity control, is shown to result in robust and high performance tracking.

The authors discuss three dominant dynamic effects that are manifested in the use of robot end-mounted cameras for high-performance tracking and positioning tasks. They are time delay (or latency in the sensing and control blocks), time-varying loop gain due to perspective, and vibrations due to structural and drive compliance. Analysis of the dynamic is presented and compared with experimental results.>

The design and implementation of a microprocessor-based system to control the interaction forces between a five-axis articulated robot and a workpiece is described. The control system worked in parallel with a robot controller by calculating position corrections that allowed forces to be controlled in the desired manner. These corrections were successfully interfaced to the controller's position control loop on an individual-axis level. Stable force-control algorithms were designed in spite of limitations imposed by flexibility in the robot drive train. For multi-degree-of-freedom force control, it is shown that each axis can be considered autonomous, obviating the need for a multivariable approach. Force control was implemented in both edge following and deburring experiments. In edge following, the commanded normal force ranged from 1 to 15 N, while the root mean square (rms) force errors remained constant. Errors increased from 0.5 to 1.5 N rms as tangential speed was increased from 1 to 9 cm s-1. The performance of the force control system during deburring operations was characterized across the full force and speed range of the cutting tools used. The smoothness of cut was shown to be consistent with manual deburring operations in terms of optimal feed and metal removal rates.

The design and implementation of a microprocessor based control system to control the interaction forces between a five axis articulated robot and a workpiece is described. The control system works in parallel with a robot controller by calculating position corrections that allow force to be controlled in the desired manner. The corrections were successfully interfaced to the position control loop on an individual axis level. Stable force control algorithms were designed in spite of limitations imposed by flexibility in the robot drive train. In the multi-degree of freedom control case it is shown that each axis can be considered autonomous, obviating the need for a multivariable approach. Control was implemented in edge following experiments. Across levels of commanded normal force ranging from 0 to 15 N, the RMS force errors remain constant. Errors increased from 0.5 N to 1.5 N RMS as tangential speed was increased from 0 to 9 cm/sec. The performance of the force control system during deburring operations is characterized across the full force and speed range of the cutting tools used. Smoothness of cut is shown to be consistent with standard deburring operations in terms of optimal feed and metal removal rates.