Elevator Group Control System Research Articles

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.

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>