In the modern era, the increase in the number of shopping malls and industrial building has led to an exponential increase in the usage of elevator systems. Thus there is an increased need for an effective control system to manage the elevator system. This paper is aimed at introducing an effective method to control the movement of the elevators by considering various cases where in the location of the person is found and the elevators are controlled based on various conditions like Load, proximity etc... This method continuously monitors the weight limit of each elevator while also making use of image processing to determine the number of persons waiting for an elevator in respective floors. Canny edge detection technique is used to find out the number of persons waiting for an elevator. Hence the algorithm takes a lot of cases into account and locates the correct elevator to service the respective persons waiting in different floors.
The geographically distributed feedback control loops connected via communication network elucidate the core of networked control system (NCS), wherein different users spread all over the world can regulate, direct and command the components of control system located at distant location. The proficiency of NCS provides sceptre to its user and multifaceted assignments are successfully endowed through it. The ascendancy of NCS is lowered through inconspicuous delays which destabilize the system. The induction of delays in the network lead to the proscription of packet delivery, bandwidth utilization and stable system response. In this manuscript Smith predictor is modified using Markov approach and Kalman estimation algorithm. The scheme has been implemented by using Matlab/ Simulink software for delay compensation. Performance analysis shows the robustness of modified Smith-Predictor controller in comparison to classical Smith predictor controller and proportional-integral-derivative based controllers.Povzetek: V prispevku je predstavljena nova tehnika za uravnavanje časovnih zaostankov v porazdeljenih nadzornih mrežnih sistemih.
By the second decade of the 21st century, there has been a multi-faceted technological development in the field of networked control system (NCS). This progression in NCS has not only revealed its significant applications in various areas but has also unveiled various difficulties associated with it that hampered the operations of networked control system. Network-induced delays are issues that promote many other issues like packet dropout and brevity in bandwidth utilization. In this research article, network-induced delay has been curtailed by using the harmony between Smith predictor and Markov approach. The error estimation of the Smith predictor controller used for the simulation is carried out through a Markov approach which allows the control of the system to operate smoothly by optimizing the control signal. To implement the proposed method, the authors have simulated a third order system in Matlab/Simulink software.
In the modern era, the escalation of vehicles on the roads has caused an increasin g need for a reliable and intelli g ent control of the traffic li g ht system. This paper is aimed at solvin g this crisis by effectively computin g the density of traffic based on the ima g es picked up by cameras placed on the traffic posts. The method involves a simple al g orithm which performs pixel elimination and detection followed by processin g usin g a fuzzy controller. It can be further extended towards hardware implementation usin g dedicated processors. Our approach involves takin g ima g es at re g ular intervals and continuously processin g them with a reference ima g e which is captured when there is no traffic (empty road).The reference ima g es are stored and used for calibration purpose. This al g orithm enables the system to infer the traffic density which is then evaluated by a fuzzy controller to determine the timin g of the traffic si g nals. The fuzzy controller consists of an output function which dynamically controls the output based on the comparison of current ima g e's pixel count correspondin g to the vehicle density.Index Terms-Fuzzy controller, Pixel elimination and detection al g orithm, output distribution function.
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