A design procedure is proposed for digital repetitive controllers satisfying (i) asymptotic rejection of a class of periodic disturbances and (ii) a sampled-data H∞ norm specification. The synthesis problem is formulated by extending the step disturbance rejection problem. A necessary condition for the periodic disturbance so that the synthesis problem has a solution is derived. The synthesis problem is finally reduced to a sampled-data H∞ control problem with a design parameter which can be used for adjusting the performance of the periodic disturbance rejection. The effectiveness of the proposed method is confirmed by a numerical example.
The use of Virtual Reality (VR) is essential to entertainment, architecture, and other industry as well as science. So, it is important to develop the cost-effective VR with the superior feeling of “Reality”. To accomplish the requirement, we have to provide human appropriate sensory stimuli to enhance the sense of reality and immersion. In human, the most part of sensory information are owing to vision, and it is sure to play an important role in VR environment. One of the important psycho-physiological effects in VR is visually induced perception of self-motion, called vection. In this study, we investigated circular vection to specify the optimal parameter for the visual stimulus, such as spatial frequency, temporal frequency, and stimulus speed. And we revealed that the induction of circular vection depended on the multiple parameter of visual stimulus. Our results are suggested that selecting fundamental parameter of visual stimuli is important to improve the human experience of reality and reduce the side effects, such as motion sickness.
In this paper, we propose a decomposition and coordination method for routing problems for multiple automated guided vehicles (AGVs) using Petri Nets. An extended Petri Net model is created to represent concurrent motion of multiple AGVs. The routing problem to minimize total transportatin time is formulated by the proposed Petri Net. The optimization model for the Petri Net is decomposed into several subproblems which can be solved by Dijkstra's algorithm in polynomial order. The effectiveness of the proposed method is evaluated by several numerical examples.
PID control schemes have been widely employed for most process systems represented by chemical processes. However, it is a very important problem how to tune PID parameters, because these parameters have a great influence on the stability and the performance of the control system. On the other hand, lots of works for the robust control have been carried out to cope with system uncertainties. Then, some PID parameter tuning methods have been proposed based on the robust stability. However, if the range of uncertainties is very large, the control performance becomes quite conservative. By the way, the support vector machine (SVM) has been proposed as one of the pattern recognition methods and gets lots of attention in last decades. The main motivation in this paper is to present a design scheme of controllers with the switching structure, in which some robust PID controllers are suitably switched using the SVM. Finally, the proposed control scheme is numerically evaluated on a simulation example.
A robust optimum design technique for the structural design of resonator-type surface acoustic wave (SAW) filters is presented. For deciding desirable structures of SAW filters based on the computer simulation, the equivalent circuit model of interdigital transducer (IDT), which includes several uncertain constant parameters, is usually used. In order to cope well with the designing imperfections caused by the inevitable dispersion of these parameters, the quality engineering technique, or the Taguchi method, combined with a genetic local search (GLS) is employed. Besides the traditional Taguchi's two-step design maximizing the robustness of products before the realization of their specified functions, the concurrent design of robustness and functions is also described.