Model based disturbance compensating methods such as disturbance observer, robust control with adaptive algorithm, enhanced internal model control are well known control structures for robust motion controller which can satisfy desired performance and robustness of high-speed/high-accuracy positioning systems. In this paper, these are analyzed in the unified framework and their design method is proposed. To do this, a generalized disturbance attenuation framework named RIC (robust internal-loop compensator) structure is introduced. Through parameterization based on RIC, it is shown that there are inherent equivalences in their structures and the proposed RIC gives a general design framework for the model based disturbance compensating methods. Through simulation, the proposed method is verified.

The tuning method of controllers can be used for effectively determining the overall performance of positioning systems. In particular, this method is highly effective in the case of high-speed and high-accuracy positioning systems. In this paper, a sliding-mode controller that uses one of the well-known approaches of robust control methodology is designed for high-speed positioning systems that require a high-accuracy performance. A performance-tuning method based on a disturbance observer (DOB) structure is also proposed. First, a generalized disturbance attenuation framework named robust internal-loop compensator (RIC) is introduced, and a sliding-mode controller based on a Lyapunov redesign is analyzed in the RIC framework. Then, the DOB properties of the sliding-mode controller are presented, and it is shown that the performance of the closed-loop system with a sliding-mode controller can be tuned up by using the structural characteristics of the DOB. These results make the design of an enhanced sliding-mode controller possible. Finally, the proposed algorithm is experimentally verified and discussed with two positioning systems. Experimental results show the effectiveness and the robustness of the proposed scheme.

A robust high-speed motion controller is proposed. The proposed controller consists of the proximate time optimal servomechanisms (PTOS) for high-speed motion, disturbance observer (DOB) for robustness, friction compensator, and saturation handling element. In the proposed controller, DOB basically provides the chance to apply PTOS to nondouble integrator systems by drastically reducing disturbances as well as unwanted signals due to difference between real system and the double integrator model. But, in DOB-based systems, if control input is saturated due to control input of PTOS and/or DOB, overall system stability cannot be guaranteed, which is first found and analyzed in this paper. To solve this problem, robust stability and internal stability conditions of DOB-based system are derived. It is also shown that DOB could violate the internal stability, when the control input is saturated. Eventually, a simple saturation handling element is inserted to maintain internal stability of overall system. Also, we explain that our two saturation handling methods, i.e., Additional Saturation Element (ASE) and Self Adjusting Saturation (SAS) are the equivalent solutions of saturation problem to maintain internal stability. The stability and performances of the proposed controller are verified through numerical simulations and experiments using a precision linear motor system. [S0022-0434(00)01103-5]

Learning affordance is very important for autonomous robots to know what the necessary actions should be performed to complete a given task with its abilities. However, itpsilas difficult to identify and apply affordances in practice for robots. In order for a robot to get benefits from this concept, this paper proposes ontology approach based affordance concept for ubiquitous robots. The goal of this affordance-based ontology effort is to develop and begin to populate a neutral knowledge representation capturing relevant information about robots capabilities and what the environment afford to assist human life in ubiquitous robots environment. We propose a new method to dasiateachpsila robot learn objects and context affordances using ontology approach for semantic robots in ubiquitous robots space.

In this paper, a novel approach of knowledge management for the space/location perceiving capacity of robots is proposed. First, the ubiquitous function services composed of smart object, smart logic, and smart discovery service are proposed in order to distribute knowledge flexibly and reliably to changing environment and also for a robot to invoke and merge the distributed knowledge more freely. Next, physical and virtual spaces are merged by RFID tags. Through this, it is shown that ambient intelligence is realized and the space localization and mapping problem of robots can be more easily solved. Finally, the experiment based on an example scenario is carried out to verify the proposed method in the informative space named u-RT space which has two kinds of RFID tags, a virtual space with ubiquitous function services realized by Web services, and a networked robot system which works in these spaces