Implementation of Neural Network Based Control Scheme on the Benchmark Conical Tank Level System

被引：0
|
作者：
Bhadra, Sanjay [1 ]
Panda, Atanu [2 ]
Bhowmick, Parijat [3 ]
Goswami, Shinjinee [4 ]
Podder, Sayan [5 ]
Dutta, Debayan [5 ]
Chowdhury, Zeet [5 ]
机构：
[1] UEM, Dept Elect Engn, Kolkata, India
[2] IEM, Dept Elect & Commun Engn, Kolkata, India
[3] Univ Manchester, Sch Elect & Elect Engn, Manchester M13 9PI, Lancs, England
[4] Netaji Subhas Engn Coll, Dept Elect & Commun Engn, Kolkata, India
[5] IEM, Dept Elect & Elect Engn, Kolkata, India
来源：
2019 IEEE 9TH ANNUAL COMPUTING AND COMMUNICATION WORKSHOP AND CONFERENCE (CCWC) | 2019年
关键词：
Conical tank; neural network; parameter estimation; adaptive neural network control; extended Kalman filter;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This paper proposes an elegant controller design technique exploiting Neural Network based adaptive control strategy. In this work, an Extended Kalman Filter algorithm has been applied to tune the controller parameters, which are actually the weights of the neural network. A case study on the water - level control of a conical tank is considered in this paper to demonstrate the application and usefulness of the proposed control scheme. From the simulation results, it is observed that the proposed neural network adaptive control scheme ensures satisfactory servo (i.e., set point tracking) and regulatory performances of the nonlinear process.
引用
收藏
页码：556 / 560
页数：5
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