Design of nonlinear control systems by means of differential genetic programming

Joe Imae, Yoshiteru Kikuchi, Nobuyuki Ohtsuki, Tomoaki Kobayashi, Guisheng Zhai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

Based on the genetic programming (GP), a new design method of optimal and/or robust controllers of nonlinear systems is proposed. First we introduce a new type of the genetic programming, which is so called "differential GP". The differential GP combines the conventional GP with an automatic differentiation scheme, so that it can solve Hamilton-Jacobi-Bellman (HJB)/Hamilton-Jacobi-Isaacs (HJI) / Francis - Byrnes - Isidori (FBI) equations. Our design method is mainly based on the differential GP technique, and so it gives us a new possibility of the HJB/HJI/FBI based design techniques. Lastly, the effectiveness of the differential GP based design method is demonstrated through some design examples of nonlinear systems.

Original languageEnglish
Title of host publicationProceedings of the IEEE Conference on Decision and Control
Pages2734-2739
Number of pages6
Volume3
Publication statusPublished - 2004
Externally publishedYes
Event2004 43rd IEEE Conference on Decision and Control (CDC) - Nassau, Bahamas
Duration: 2004 Dec 142004 Dec 17

Other

Other2004 43rd IEEE Conference on Decision and Control (CDC)
CountryBahamas
CityNassau
Period04/12/1404/12/17

Fingerprint

Nonlinear control systems
Genetic programming
Nonlinear systems
Controllers

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Safety, Risk, Reliability and Quality
  • Chemical Health and Safety

Cite this

Imae, J., Kikuchi, Y., Ohtsuki, N., Kobayashi, T., & Zhai, G. (2004). Design of nonlinear control systems by means of differential genetic programming. In Proceedings of the IEEE Conference on Decision and Control (Vol. 3, pp. 2734-2739)

Design of nonlinear control systems by means of differential genetic programming. / Imae, Joe; Kikuchi, Yoshiteru; Ohtsuki, Nobuyuki; Kobayashi, Tomoaki; Zhai, Guisheng.

Proceedings of the IEEE Conference on Decision and Control. Vol. 3 2004. p. 2734-2739.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Imae, J, Kikuchi, Y, Ohtsuki, N, Kobayashi, T & Zhai, G 2004, Design of nonlinear control systems by means of differential genetic programming. in Proceedings of the IEEE Conference on Decision and Control. vol. 3, pp. 2734-2739, 2004 43rd IEEE Conference on Decision and Control (CDC), Nassau, Bahamas, 04/12/14.
Imae J, Kikuchi Y, Ohtsuki N, Kobayashi T, Zhai G. Design of nonlinear control systems by means of differential genetic programming. In Proceedings of the IEEE Conference on Decision and Control. Vol. 3. 2004. p. 2734-2739
Imae, Joe ; Kikuchi, Yoshiteru ; Ohtsuki, Nobuyuki ; Kobayashi, Tomoaki ; Zhai, Guisheng. / Design of nonlinear control systems by means of differential genetic programming. Proceedings of the IEEE Conference on Decision and Control. Vol. 3 2004. pp. 2734-2739
@inproceedings{6269d1edde69476b823e9c208e384128,
title = "Design of nonlinear control systems by means of differential genetic programming",
abstract = "Based on the genetic programming (GP), a new design method of optimal and/or robust controllers of nonlinear systems is proposed. First we introduce a new type of the genetic programming, which is so called {"}differential GP{"}. The differential GP combines the conventional GP with an automatic differentiation scheme, so that it can solve Hamilton-Jacobi-Bellman (HJB)/Hamilton-Jacobi-Isaacs (HJI) / Francis - Byrnes - Isidori (FBI) equations. Our design method is mainly based on the differential GP technique, and so it gives us a new possibility of the HJB/HJI/FBI based design techniques. Lastly, the effectiveness of the differential GP based design method is demonstrated through some design examples of nonlinear systems.",
author = "Joe Imae and Yoshiteru Kikuchi and Nobuyuki Ohtsuki and Tomoaki Kobayashi and Guisheng Zhai",
year = "2004",
language = "English",
volume = "3",
pages = "2734--2739",
booktitle = "Proceedings of the IEEE Conference on Decision and Control",

}

TY - GEN

T1 - Design of nonlinear control systems by means of differential genetic programming

AU - Imae, Joe

AU - Kikuchi, Yoshiteru

AU - Ohtsuki, Nobuyuki

AU - Kobayashi, Tomoaki

AU - Zhai, Guisheng

PY - 2004

Y1 - 2004

N2 - Based on the genetic programming (GP), a new design method of optimal and/or robust controllers of nonlinear systems is proposed. First we introduce a new type of the genetic programming, which is so called "differential GP". The differential GP combines the conventional GP with an automatic differentiation scheme, so that it can solve Hamilton-Jacobi-Bellman (HJB)/Hamilton-Jacobi-Isaacs (HJI) / Francis - Byrnes - Isidori (FBI) equations. Our design method is mainly based on the differential GP technique, and so it gives us a new possibility of the HJB/HJI/FBI based design techniques. Lastly, the effectiveness of the differential GP based design method is demonstrated through some design examples of nonlinear systems.

AB - Based on the genetic programming (GP), a new design method of optimal and/or robust controllers of nonlinear systems is proposed. First we introduce a new type of the genetic programming, which is so called "differential GP". The differential GP combines the conventional GP with an automatic differentiation scheme, so that it can solve Hamilton-Jacobi-Bellman (HJB)/Hamilton-Jacobi-Isaacs (HJI) / Francis - Byrnes - Isidori (FBI) equations. Our design method is mainly based on the differential GP technique, and so it gives us a new possibility of the HJB/HJI/FBI based design techniques. Lastly, the effectiveness of the differential GP based design method is demonstrated through some design examples of nonlinear systems.

UR - http://www.scopus.com/inward/record.url?scp=14244264344&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=14244264344&partnerID=8YFLogxK

M3 - Conference contribution

VL - 3

SP - 2734

EP - 2739

BT - Proceedings of the IEEE Conference on Decision and Control

ER -