Group Control System Research Articles

Sistema de control inteligente para un grupo de elevadores

En este artículo se trata el problema del tráfico vertical en edificios de gran altura y se describe el análisis, diseño y evaluación de un sistema de control para un grupo elevadores que busca mejorar el desempeño respecto a un sistema de control tradicional. El controlador propuesto busca asignar de una forma inteligente las llamadas que se generan a los ascensores que hacen parte del grupo, el desempeño del sistema se traduce en una reducción de los tiempos de servicio y de la energía que invierte el sistema. El controlador propuesto está basado en lógica difusa y las reglas de inferencia expresan el conocimiento de un experto orientado hacia la obtención de los objetivos mencionados. El controlador inteligente se evalúa en un simulador gráfico desarrollado para este fin, este simulador permite ingresar parámetros de configuración para que se adapte y represente una edificación real. Se corrieron dos simulaciones, una usando un controlador convencional y otra usando el controlador inteligente, esto con el fin de comparar su desempeño y cuantificar valores como tiempo de esperar de los usuarios y energía consumida por el sistema.

A Double-Deck Elevator Group Supervisory Control System Using Genetic Network Programming

Elevator group supervisory control systems (EGSCSs) are designed so that the movement of several elevators in a building is controlled efficiently. The efficient control of EGSCSs using conventional control methods is very difficult due to its complexity, so it is becoming popular to introduce artificial intelligence (AI) technologies into EGSCSs in recent years. As a new approach, a graph-based evolutionary method named genetic network programming (GNP) has been applied to the EGSCSs, and its effectiveness is clarified. The GNP can introduce various a priori knowledge of the EGSCSs in its node functions easily, and can execute an efficient rule-based group supervisory control that is optimized in an evolutionary way. Meanwhile, double-deck elevator systems (DDESs) where two cages are connected in a shaft have been developed for the rising demand of more efficient transport of passengers in high-rise buildings. The DDESs have specific features due to the connection of cages and the need for comfortable riding; so its group supervisory control becomes more complex and requires more efficient group control systems than the conventional single-deck elevator systems (SDESs). In this paper, a new group supervisory control system for DDESs using GNP is proposed, and its optimization and performance evaluation are done through simulations. First, optimization of the GNP for DDSEs is executed. Second, the performance of the proposed method is evaluated by comparison with conventional methods, and the obtained control rules in GNP are studied. Finally, the reduction of space requirements compared with SDESs is confirmed.

Employment and Market Innovation in Chinese Business Group Affiliated Firms: The Role of Group Control Systems

Prior research has suggested a number of potential benefits to firm membership in business groups. These benefits include availability of capital and other resources not readily accessible in an open market, the facilitation of entrepreneurship, plus information and risk sharing advantages. We suggest that another important benefit is the assistance of group control systems in helping the firm to manage conflicting pressures in the institutional environment and facilitate coevolution of these conflicting pressures. To empirically demonstrate the relevance of this viewpoint, we examine the case of China where business groups facilitate institutional transition, actively balancing market pressures to increase levels of innovativeness in firms with institutional pressures emanating from the government to maintain high employment levels. Using data from a broad sample of more than 1,000 Chinese affiliate firms in more than 200 business groups, we find that government policy, ownership and managerial mindset influence the political goal of maintaining high employment levels, while interdependence among group affiliate firms is related to lower employment levels. However, while government ownership and the government managerial mindset were negatively related to market innovation activities, group financial and cultural control systems positively affected the tendency of affiliate firms to focus on market innovation.

Distributed approach to group control of elevator systems using fuzzy logic and FPGA implementation of dispatching algorithms

Elevator systems are administrated by an elevator group control system (EGCS) and micro-processed sub-systems implementing a local control system (LCS) for each elevator. This paper describes the validation of five dispatching algorithms for elevator systems that were implemented on Spartan 3 FPGA-based boards in an integrated approach reducing the area and improving performance. The overall system is composed of several LCS, which implement the dispatching algorithms, an RS485-based network and a virtual environment called virtual elevator interface system (VEI), which includes a simulator/monitoring system and an EGCS-based on fuzzy logic (FEGCS). The FEGCS runs on a PC and, under different traffic situations, determines the best algorithm to be run in each LCS in order to reduce the user waiting time and the power consumption. The novelty of this approach is that the LCSs are capable to run different dispatching algorithms independently, that are suitable for specific passenger traffic situations, while the FEGCS only must determine the best algorithm to be run in each LCS. The VEI allows the designer to test and validate in a flexible way the algorithm performance for different traffic situations.

Evolutionary bi-objective optimisation in the elevator car routing problem

The paper introduces a genetic algorithms based elevator group control system utilising new approaches to multi-objective optimisation in a dynamically changing process control environment. The problem of controlling a group of elevators as well as the basic principles of the existing single-objective genetic elevator group control method are described. The foundations of the developed multi-objective approach, Evolutionary Standardised-Objective Weighted Aggregation Method, with a PI-controller operating as an interactive Decision Maker, are introduced. Their operation as a part of bi-objective genetic elevator group control is presented together with the performance results obtained from simulations concerning a high-rise office building. The results show that with this approach it is possible to regulate the service level of an elevator system, in terms of average passenger waiting time, so as to bring it to a desired level and to produce that service with minimum energy consumption. This has not been seen before in the elevator industry.

The modelling and simulation of elevator group control sytems for public service buildings

Elevator traffic control systems have become more and more complicated due to their nature of intelligence. Artificial intelligence methods employing neural networks have been proved to be successful in many fields, such as process modeling, pattern recognition and classification problems. They have also been applied to basic problems in elevator traffic control systems, such as the prediction and control of elevator movements. In particular, neural networks can offer better solutions to the passenger call allocation process when compared to the classical traffic control methods. Elevator control algorithms utilizing neural networks aims at distributing the most suitable cars to the floors by considering the passenger service demand. Neural networks can dynamically learn the behavior of an elevator system and predict the next floors to stop, based on what has been learnt. In this paper the neural network approach has been applied to Duplex/Triplex group control systems for improving passenger waiting time and a lift simulation software has been developed and implemented in order to assess the learning capability by measuring the performance of the control algorithm. The lift traffic analysis have been carried out by examining the simulation results obtained.

Elevator group control system using multiagent system

AbstractIn this study, the authors proposed an elevator group control system using multiagent system, and verified the efficiency of the system in areas characterized by concentration of large crowds of passengers on the main floor, for example, during morning rush‐hour traffic. Congestion on the main floor in heavy morning rush‐hour traffic areas was previously alleviated using specific traffic control systems providing so‐called morning rush‐hour operation by forced dispatching of multiple elevators to the main floor. However, since forced dispatching on the main floor affects areas other than the main floor and also the subsequent service on the main floor, it makes overall improvement of transportation efficiency a difficult task. There are published reports relating to morning rush‐hour operation, but these deal with centralized control based on overall monitoring and sending instruction commands. Thus, the problem is that if this control system stopped working, it caused overall malfunctioning. In addition, in a system based on overall monitoring and generating optimal control plan in accordance with the received information, it is not easy to generate design updates following a change in the system's design or environment. Therefore, in the current study the authors introduced a multiagent system with distributed processing, in which individual elevators make action decisions by independent learning process. The authors proposed an elevator group control system which uses simplified reasoning to provide for flexible response even in the case of a changed environment, such as when a part of the elevator group has stopped functioning. © 2002 Wiley Periodicals, Inc. Syst Comp Jpn, 34(1): 45–58, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.1183

Theoretical Control and Experimental Verification of Carded Web Density. Part IV: Computer-Aided On-Line Control of Carded Web Density

This paper presents a new on-line control system that is implemented for controlling carded web density. The control system is based on the previous controller design of the worker-stripper group presented in Parts I, II, and III of this series. Theoretically, these aforementioned control methods can make a corresponding closed-loop system for efficient and precise system control, but the design effort is meaningful only when tested by experiment. In this part of the series, the well-designed analog controller can be discretized and used as a digital controller for experimental verification. The worker-stripper group control system successfully operates based on our experimental implementation and agrees well with theoretical analyses.

Adaptive elevator group control with cameras

A new elevator group control system is proposed. The system learns dynamic traffic flows by analyzing passenger traffic without prespecified patterns. A genetic algorithm continuously generates dispatch functions according to changes in passenger traffic. By considering the status inside elevators, the directions of passenger movement, and the number of waiting passengers, the system occasionally allocates multiple elevators for a single hall call, which assists in reducing passengers' waiting time. Experimental results showed up to 25% improvement over a system without the above features.

A parameter tuning method for an elevator group control system using a genetic algorithm

This paper describes a new parameter tuning method for an elevator group control system. In such a system, tuning parameters describing elevator use and the building environment are important. The new tuning method uses improved genetic algorithms to follow environment changes and to give robustness. Keeping diversity is important in following environment changes. The paper also describes the addition of the random chromosome method and addition of other estimation methods to maintain diversity. Their effects are shown by simulations. © 1998 Scripta Technica, Electr Eng Jpn, 124(1), 55–64, 1998

Design and implementation of a fuzzy elevator group control system

Elevator group control systems (EGCSs) are the control systems that systematically manage three or more elevators in order to efficiently transport passengers. Most EGCSs have used the hall call assignment method to assign elevators in response to passengers' calls. This paper proposes a control strategy generation method, a hall call assignment method based on the fuzzy theory, and then the fuzzy elevator group control system (FEGCS). The control strategy of FEGCS is made using the classification of the passenger traffic and system manager's requirements, and the hall calls are assigned to suitable elevators by the generated control strategy. The system is operated using the given control strategy which is defined by the system manager. The proposed system shows better results than the conventional methods in simulations.

An elevator group control system with floor-attribute control method and system optimization using genetic algorithms

A new concept is proposed for an elevator group control system which can change control settings according to individual floor utilization situations. The floor-attribute-based control method uses a combination of floor-attribute-based evaluation and car-attribute-based evaluation. Computer simulations show it can improve multiple preferential door settings at the same time. Additionally, an on-line parameter tuning method using genetic algorithms is proposed. The floor attribute control method needs several dozen control parameters to be tuned according to each building's traffic, and the proposed method can do it. The elitist-preserving strategy is an effective way to keep control stability. A diversity-recovering operation, which initializes population, excluding the elitist individual, when traffic flow data have changed, improves the following ability for transitions of utilized conditions.

Dynamical Complex System. A Parameter Tuning Method for Elevator Group Supervisory Control System By Using Genetic Algorithms.

This paper describesa new parameter tuning method for an elevator group control system. In an elevator group control system tuning parameters describing elevator use and the building environment are important. The new tuning method uses improved genetic algorithms to follow environment changes and to give robustness. Keeping diversity is important in following environment changes. The paper also describes the adding random chromosomes method and adding other estimationsmethod to keep diversity. Their effects are shown by simulations.

The Role of Production Control in the Development of Burnout

Burnout is an increasingly important problem in modern work organizations. Few studies, however, have explicitly applied an adequate theoretical understanding of the performance of modern organizations. This article aims to initiate both a discussion of this phenomenon and higher-quality research into the emergence of burnout based on an understanding of the economic-technological rationalization and control (management control) of production and service processes. In applying production control, both technical and bureaucratic, group and attitudinal control systems are increasingly integrated. This so-called systematic control strategy is one of the major causes of burnout. The cumulative effect of an increasing workload combined with reduced resources due to economic considerations and technocratic implementation of production control is assumed to be relevant to the development of burnout. The authors' propositions apply to service workers in human service organizations and to key workers in enterprises using flexible specialization combined with self-directed work groups.

Production management for group control system using the PC LAN

Production management for group control system using the PC LAN

A fuzzy approach to elevator group control system

The elevator group control systems are the control systems that manage systematically, three or more elevators in order to efficiently transport the passengers. In the elevator group control system, the area-weight which determines the load biases of elevators is a control parameter closely related to the system performance. This correspondence proposes a fuzzy model based method to determine the area weight. The proposed method uses a two-stage fuzzy inference model which is built by the study of area-weight properties and expert knowledge. The proposed method shows more desirable results than the conventional method in simulations that use real traffic data.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Alterations in the follow-up circuit of the speed changer of �RG-M turbine speed governors for operation in the active power group control system

1. Alteration of the follow-up circuit of the SC in the type EGR-M SG during operation of the units in a group control system provides the possibility of smooth transfer of the unit out of the APGC system, which increases the operating reliability of the APGC system in an overcurrent control regime and in eliminating emergency situations. 2. After an additional check, the alteration of the follow-up circuit of the SC can be used for a second modification of the type EGR-2M governors of turbines.

Progress of elevator supervisory group control system.

Progress of elevator supervisory group control system.

A Group Control System of Elevators Using Fuzzy Rule-Base

A Group Control System of Elevators Using Fuzzy Rule-Base

SYSTEM CONCEPT AND CRITERIA FOR BATTLE GROUP DECISION MAKING

ABSTRACTThe command and control system problem associated with the battle group, an ad hoc assemblage of naval resources, with the mission of achieving a predetermined objective as assigned by higher authority, is discussed. After restatement of the problem, criteria for evaluating system concepts are proposed. Emphasis is placed on combat environments.A concept for development of a battle group command and control system consistent with existing command philosophy and functional partition is presented. The philosophic principle is command by exception in a multi‐hierarchical structure. Functional partition into warfare areas such as ASW, AAW, and ASUW provides the basis for the multiple branches of the hierarchy.Finally, the system criteria are applied to the battle group command and control concept presented herein. The resulting evaluation demonstrates that the conceptual system is readily implementable and can meet battle group operational needs.