This paper focuses on a quality-of-service (QoS)-based remote control scheme for networked control systems via the Profibus token passing protocol. Typically, token passing experiences random network delay due to uncertainties in token circulation, but the protocol has in-built upper and lower bounds of network delay. Thus, to ensure the control performance of networked control systems via the Profibus token passing protocol, the network delay should be maintained below the allowable delay level. As the network delay is affected by protocol parameters, such as target rotation time, we present here an algorithm for selection of target rotation time using a genetic algorithm to ensure QoS of control information. We also discuss the performance of the QoS-based remote control scheme under conditions of controlled network delay. To evaluate its feasibility, a networked control system for a feedback control system using a servo motor was implemented on a Profibus-FMS network.

Misalignment can be an important error source in the integration of the global positioning system (GPS) and inertial navigation systems. This paper presents car test results on the estimation of alignment errors in the integration of a low-grade inertial measurement unit (IMU) with accurate GPS measurement systems. The car test was conducted with a low-cost solid-state IMU and carrier-phase differential GPS measurement systems. Test results showed that changes in the angular velocity improve the estimation of the lever arm between the GPS antenna and IMU. They also showed that changes in acceleration improve the estimation of the relative attitude between the GPS antenna array and IMU. The lever arm was estimated with a 10-cm error. The relative attitude was estimated with a half-degree error. An iterative scheme was used to improve the estimation of the alignment errors during postprocessing. The scheme was shown to be useful when the test car could not have sufficient changes in motion due to limitations in its path. With the given set of test data, the estimation error decreased as the number of iterations increased.

This paper presents how the control performance of the feature-based visual servo system is improved by utilizing redundant features. The effectiveness of the redundant features is evaluated by the smallest singular value of the image Jacobian which is closely related to the accuracy in the world coordinate system. Usefulness of the redundant features is verified by the real time experiments. To investigate the accuracy of the redundant visual servo control, real time experiments on the dual-arm robot with eight joints are carried out. The rotation and translation step responses with three, four and five features are examined.

In this paper, the localization of a mobile robot using images of a moving target is introduced. Typical objects are stored in the database for the localization of the mobile robot. With a fixed camera, a perspective camera model and a given object database, an image frame can provide the pose (distance and orientation) of the object with respect to the camera. Utilizing the consecutive image frames and motion estimation technology, the relative pose of the object with respect to the camera can be obtained accurately; and during the process, calibration of camera with respect to the world frame, i.e. localization of a mobile robot, is gradually performed. This localization scheme is demonstrated by the experiments.

We present an approach to visual feedback control using image-based visual servoing with stereo vision. In order to control the position and orientation of a robot with respect to an object, a technique is proposed using binocular stereo vision. The stereo vision enables us to calculate an exact image Jacobian not only at around a desired location but also at the other locations. The suggested technique can guide a robot manipulator to the desired location without giving such priori knowledge as the relative distance to the desired location or the model of an object even if the initial positioning error is large. The paper describes a model of stereo vision and how to generate feedback commands. The performance of the proposed visual servoing system is illustrated by the simulation and experimental results and compared with the case of conventional method for an assembling robot.

This paper introduces an effective method to integrate optimization and control of major plant processes with strong couplings between them. The proposed integration philosophy that consists of the cause-effect relation decides upon control setpoints for the individual processes by optimizing a global objective function which aims at improving process yield. The objective is to maximize productivity and, at the same time, reduce defects in each of the subsequent operations. A textile plant is considered as a testbed and three processes-warping, slashing and weaving, are employed to illustrate the feasibility of the approach. The supervisory level of the control architecture is intended to continuously improve the control setpoints depending upon feedback information from the weave room, slasher operator and warping data.

Polishing work of a freely-curved surface die demands simple and repetitive operations but requires a considerable amount of time for high precision. Some workers tend to gradually avoid the polishing work because of the poor environment caused by dust and noise. In order to reduce the polishing time and solve the problem of the shortage of skilled workers, an automatic polishing system should be developed. In this study, a user-friendly automatic polishing system was developed. It is composed of two different systems: a three-axis machining center and a two-axis polishing robot. The developed polishing system with five degrees of freedom is able to keep the polishing tool normal to the die surface. In order to operate the polishing system, the host computer should transmit the polishing data to the FANUC controller of the machining center and DSP controller of the polishing robot, respectively. A driving program (P-PROS: Pusan National University-polishing robot operating system) in the Windows environment was developed to easily operate the polishing robot system. A communication program was developed for transmitting the polishing data to each controller. To evaluate the performance of the P-PROS and the developed DSP (digital signal processing) controller, a polishing experiment on the shadow-mask die was done.

Presents an approach to the design and real-time implementation of an adaptive controller for a robotic manipulator based on digital signal processors. The Texas Instruments DSP (TMS320C31) chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for robotic manipulators. In the proposed scheme, adaptation laws are derived from the direct model reference adaptive control principle based on the improved Lyapunov second method. The proposed adaptive controller consists of an adaptive feedforward and feedback controller and PI-type time-varying auxiliary control elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for an industrial robot with four joints in the joint space and Cartesian space.

Presents a stabilizing controller design method for flexible joint robot manipulators, which incorporates an additional stabilizing control law with the sliding property. The simulations of a 2-D/O/F/ flexible joint manipulator show that the proposed scheme is effective for manipulators with highly flexible joints.