1,567 research outputs found
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 brief review on vertical transportation research and open issue
Book of Proceedings of the International Joint Conference-CIO-ICIEOM-IIE-AIM (IJC 2016), "XX Congreso de IngenierÃa de Organización", "XXII International Conference on Industrial Engineering and Operations Management, "International IISE Conference 2016, "International AIM Conference 2016". Donostia-San Sebastian (Spain), July 13-15, 2016Vertical transportation refers to the movements of people in buildings.
High-rise buildings have emerged as a common construction nowadays. In such
buildings, the vertical transportation is extremely difficult to manage, specially,
when the people arrive at the same time at specific floors wanting to travel to other
floors. To solve such situations, the installation of elevator group control systems
(EGCS) is a usual practice. EGCS are used to manage multiple elevators in a building
to efficiently transport passengers. EGCSs need to meet the demands by assigning
an elevator to each landing call while optimizing several criteria. This paper
reviews the most relevant contributions in vertical transportation industr
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
Simulation of a four-car elevator operation using MATLAB
The design and simulation of a four-cars-elevator controller in a nine storey building is described in this paper. The design and simulation were accomplished using MATLABTM fuzzy logic toolbox. The logic of the controller of a multi-car elevator has to be designed in such a way that the average waiting time is minimized while keeping the energy consumption of the system optimum. This is a multi-criteria optimization problem in stochastic environment and is best approached through Artificial Intelligent techniques. The work here focuses mainly on extracting the rules to minimize factors (i.e. waiting time, travelled distance and riding time) in order to minimize the energy consumed by the system. In this paper a detailed algorithm is presented to achieve the multiple objectives of minimizing the waiting time and the distance travelled simultaneously. This was accomplished by distributing different weightage to different quantities and then minimizing a combined cost. A simulator has been built with interactive GUI in Matlab to evaluate the efficacy of the algorithm
Simulation of a four-car elevator operation using MATLAB
The design and simulation of a four-cars-elevator controller in a nine storey building is described in this paper. The design and simulation were accomplished using MATLABTM fuzzy logic toolbox. The logic of the controller of a multi-car elevator has to be designed in such a way that the average waiting time is minimized while keeping the energy consumption of the system optimum. This is a multi-criteria optimization problem in stochastic environment and is best approached through Artificial Intelligent techniques. The work here focuses mainly on extracting the rules to minimize factors (i.e. waiting time, travelled distance and riding time) in order to minimize the energy consumed by the system. In this paper a detailed algorithm is presented to achieve the multiple objectives of minimizing the waiting time and the distance travelled simultaneously. This was accomplished by distributing different weightage to different quantities and then minimizing a combined cost. A simulator has been built with interactive GUI in Matlab to evaluate the efficacy of the algorithm
Una revisión del estado del arte de los problemas asociados al transporte vertical mediante ascensores en edificios
El transporte vertical es una disciplina que estudia los movimientos de personas en edificios. Los edificios altos se han convertido en una construcción común hoy en dÃa. En dichos edificios, el transporte vertical es un problema que requiere un enfoque
sistemático y ordenado. AsÃ, para casos extremos en determinados edificios singulares, la ordenación del transporte vertical se
convierte en un problema muy difÃcil de manejar, especialmente cuando diferentes personas llegan casi al mismo tiempo a plantas
especÃficas deseando viajar hasta otras plantas de destino. Para resolver tales situaciones, la instalación de sistemas de control de
grupos de ascensores (conocidos en inglés como Elevator Group Control Systems, EGCS) es una práctica habitual. Los EGCS se
utilizan para gestionar ascensores coordinados múltiples en un edificio con el objeto de transportar pasajeros de manera eficiente.
Los EGCS deben satisfacer las demandas asignando un ascensor a cada llamada de planta, realizando el despacho de ascensores
atendiendo a diferentes criterios de optimización. Este artÃculo realiza una revisión sistemática y muestra distintas clasificaciones
de las contribuciones más relevantes en la industria del transporte vertical, abordando tanto la revisión de la literatura cientÃfica,
como las patentes en la industria y los trabajos recogidos en revistas de carácter profesional.Plan Nacional de I+D TI-331/2002Plan Nacional de I+D DPI2010- 15352ConsejerÃa de Innovación, Ciencia y Empresa de la Junta de AndalucÃa P07-TEP-0283
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 transportationConsejerÃa de Innovación, Ciencia y Empresa, Junta de AndalucÃa P07-TEP-02832, Spain
Applications of Soft Computing in Mobile and Wireless Communications
Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications
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
Submodular Function Maximization for Group Elevator Scheduling
We propose a novel approach for group elevator scheduling by formulating it
as the maximization of submodular function under a matroid constraint. In
particular, we propose to model the total waiting time of passengers using a
quadratic Boolean function. The unary and pairwise terms in the function denote
the waiting time for single and pairwise allocation of passengers to elevators,
respectively. We show that this objective function is submodular. The matroid
constraints ensure that every passenger is allocated to exactly one elevator.
We use a greedy algorithm to maximize the submodular objective function, and
derive provable guarantees on the optimality of the solution. We tested our
algorithm using Elevate 8, a commercial-grade elevator simulator that allows
simulation with a wide range of elevator settings. We achieve significant
improvement over the existing algorithms.Comment: 10 pages; 2017 International Conference on Automated Planning and
Scheduling (ICAPS
- …