Dynamic fuzzy logic elevator group control system for energy optimization

High-rise buildings with a considerable number of elevators represent a major logistic problem concerning saving space and time due to economic reasons. For this reason, complex Elevator Group Control Systems are developed in order to manage the elevators properly. Furthermore, the subject of energy is acquiring more and more industrial relevance every day as far as sustainable development is concerned. In this paper, the first entirely dynamic Fuzzy Logic Elevator Group Control System to dispatch landing calls so as to minimize energy consumption, especially during interfloor traffic, is proposed. The fuzzy logic design described here constitutes not only an innovative solution that outperforms usual dispatchers but also an easy, cheap, feasible and reliable solution, which is possible to be implemented in real industry controllers

A particle swarm optimization algorithm for optimal car-call allocation in elevator group control systems

High-rise buildings require the installation of complex elevator group control systems (EGCS). In vertical transportation, when a passenger makes a hall call by pressing a landing call button installed at the floor and located near the cars of the elevator group, the EGCS must allocate one of the cars of the group to the hall call. We develop a Particle Swarm Optimization (PSO) algorithm to deal with this car-call allocation problem. The PSO algorithm is compared to other soft computing techniques such as genetic algorithm and tabu search approaches that have been proved as efficient algorithms for this problem. The proposed PSO algorithm was tested in high-rise buildings from 10 to 24 floors, and several car configurations from 2 to 6 cars. Results from trials show that the proposed PSO algorithm results in better average journey times and computational times compared to genetic and tabu search approaches

An expert system for wind shear avoidance

A study of intelligent guidance and control concepts for protecting against the adverse effects of wind shear during aircraft takeoffs and landings is being conducted, with current emphasis on developing an expert system for wind shear avoidance. Principal objectives are to develop methods for assessing the likelihood of wind shear encounter (based on real-time information in the cockpit), for deciding what flight path to pursue (e.g., takeoff abort, landing go-around, or normal climbout or glide slope), and for using the aircraft's full potential for combating wind shear. This study requires the definition of both deterministic and statistical techniques for fusing internal and external information , for making go/no-go decisions, and for generating commands to the manually controlled flight. The program has begun with the development of the WindShear Safety Advisor, an expert system for pilot aiding that is based on the FAA Windshear Training Aid; a two-volume manual that presents an overview , pilot guide, training program, and substantiating data provides guidelines for this initial development. The WindShear Safety Advisor expert system currently contains over 200 rules and is coded in the LISP programming language

GA tuning of pitch controller for small scale MAVs

The paper presents the application of intelligent tuning methods for the control of a prototype MAV in order to address problems associated with bandwidth limited actuators and gust alleviation. Specifically, as a proof of concept, the investigation is focused on the pitch control of a MAV. The work is supported by experimental results from wind tunnel testing that shows the merits of the use of Genetic Algorithm (GA) tuning techniques compared to classical, empirical tuning methodologies. To provide a measure of relative merit, the controller responses are evaluated using the ITAE performance index. In this way, the proposed method is shown to induce far superior dynamic performance compared to traditional approaches

Improving the Efficiencies of Elevator Systems Using Fuzzy Logic

This research presents the application of fuzzy logic in elevators. This analyzes the features of elevators and how fuzzy logiccould be used to minimize the waiting time, detect when the temperature is high for the car, and determine which floor hashighest number of people waiting for the car. High rising building is a common sight in most of the cities today. Fast andefficient elevator transportation is a key feature when creating these kinds of buildings. As the complexity of a systemincreases, it becomes more difficult and eventually impossible to make a precise statement about its behaviour. Many of thesystems build before fuzzy logic use trial and error and effort had to be done over and over to arrive at effective control.Fuzzy logic concepts are used to enable the elevator control system to make decisions. The design criteria include ofoptimizing movement of elevators with regard to several factors such as waiting time, riding time, energy, load, etc.Software simulation is done in order to capture the performance of the proposed system which is compared to conventionalapproaches.Keywords: Fuzzy logic (FL), Elevator. Car, Software simulation

Elevator controller based on implementing a random access memory in FPGA

Previous techniques of elevator controllers suffer from two main challenges: processing time, and software size. In this work these challenges have been overcame by implementing a controller random access memory (RAM) in a fast FPGA for a proto-type of two-floors elevator, as known the RAM and FPGA are fast devices. A look-up-table LUT (which is fast technique) has been proposed for this work, this LUT has represented a proposed relation between 10 and 7 lines, the states of the sensors and switches have been represented by the 10 input lines, and the commands for the motors of slide door and traction machine have been represented by the 7 output lines. The proposed LUT has been schematically realize by a (10×7) bits RAM which has been implemented in field programmable gate arrays (FPGA). The proposed system has been performed using 'ISE Design Suit' software package and FPGA Spartan6 SP-605 evaluation kit, the clock frequency of this FPGA is 200 MHz which is respectively high. The processing time and software size of the proposed controller had reached to 20ns and 3.75 MB, which they are less than that obtained from the results of previous techniques

Vertical transportation in buildings

Nowadays, the building industry and its associated technologies are experiencing a period of rapid growth, which requires an equivalent growth regarding technologies in the field of vertical transportation. Therefore, the installation of synchronised elevator groups in modern buildings is a common practice in order to govern the dispatching, allocation and movement of the cars shaping the group. So, elevator control and management has become a major field of application for Artificial Intelligence approaches. Methodologies such as fuzzy logic, artificial neural networks, genetic algorithms, ant colonies, or multiagent systems are being successfully proposed in the scientific literature, and are being adopted by the leading elevator companies as elements that differentiate them from their competitors. In this sense, the most relevant companies are adopting strategies based on the protection of their discoveries and inventions as registered patents in different countries throughout the world. This paper presents a comprehensive state of the art of the most relevant recent patents on computer science applied to vertical transportationConsejería de Innovación, Ciencia y Empresa, Junta de Andalucía P07-TEP-02832, Spain

Computer Simulation Aided Study of a Real-time Energy Benchmarking Parameter for Lift Systems under different Traffic Control Schemes

At present, there are benchmarking procedures to assess the energy performance of lifts, e.g. VDI (4707-1/2) adopted in Germany as a pioneer, then replaced by ISO (BS EN ISO 25745-1:2012 and 25745-2:2015) in Europe, and the other in Hong Kong adopted by The Hong Kong Special Administrative Region (HKSAR) Government. The Hong Kong procedure focuses on the design performance of lift drives. The ISO standard further estimates the annual energy. To facilitate real time monitoring of energy performance of lift systems, a holistic normalization method (So et al 2005, Lam et al 2006) was developed more than ten years ago, which can simultaneously assess both drive efficiency and traffic control performance on a real-time basis, termed which is the name of the parameter measured in unit, J/kgm, and is now adopted by the HKSAR Government as a good practice in the Technical Guidelines of the Energy Code, but not yet enforced in the mandatory code. Values, not just the procedures, for benchmarking are demanded. In this article, such a parameter is evaluated under different drives and lift traffic control scenarios by using computer simulations, with the aim of arriving at a reasonable figure for benchmarking an energy efficient lift system with both an efficient drive as well as an efficient supervisory traffic control. This parameter could also be used to compare the performance of different types of intelligent car dispatchers. The simulation suggested a value of 50 J/kgm as acceptable while 40 J/kgm as good