Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

Browse

Filters

2012 - 20192

Settings

Subject: search.filters.subject.Matlab

Search Results

Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    A scalable cloud platform using matlab distributed computing server integrated with HDFS
    (IEEE Computer Society help@computer.org, 2012) Dutta, R.; Annappa, B.
    The Hadoop Distributed File System (HDFS) is a large data storage system which exhibits several features of a good distributed file system. In this paper we integrate Matlab Distributed Computing Server (MDCS) with HDFS to build a scalable, efficient platform for scientific computations. We use an FTP server on top of HDFS for data transfer from the Matlab system to HDFS. The motivation of using HDFS for storage with MDCS is to provide an efficient, fault-tolerant file system and also to utilize the resources efficiently by making each system serve as both data node for HDFS and worker for MDCS. We test the storage efficiency of HDFS and compare with normal file system for data transfer operations through MDCS. © 2012 IEEE.
  • No Thumbnail Available
    Item
    A comparative study of stanley, lqr and mpc controllers for path tracking application (adas/ad)
    (Institute of Electrical and Electronics Engineers Inc., 2019) Vivek, K.V.; Sheta, M.A.; Gumtapure, V.
    This paper presents comparative study between Stanley, LQR (Linear Quadratic Regulator) and MPC (Model Predictive Controller) controllers for path tracking application, which is a level 4 automation feature under ADAS/AD (Advanced Driver Assistance System/Autonomous Driving). The accuracy associated with all the controllers are compared by making the vehicle model run in a prescribed environment. The initial designs are done in MATLAB environment and later they are interfaced with IPG CarMaker vehicle simulation tool for fine tuning. Stanley controller is more of an intuitive steering control law where as LQR and MPC are more advanced optimal controllers. The control actions are calculated by optimising the states of the model. Kinematic vehicle model is used with states as errors and a comparator design is made to find the deviation of the vehicle from the prescribed path. The paper gives a detailed idea about the controllers regarding its use, advantages and limitations in this application. © 2019 IEEE.