Minimum time trajectory learning

Author

Sadegh, N. ; Driessen, B.

Author_Institution

Sch. of Mech. Eng., Georgia Inst. of Technol., Atlanta, GA, USA

Volume

2

fYear

1995

fDate

21-23 Jun 1995

Firstpage

1350

Abstract

This paper presents an algorithm for finding the minimum time trajectory of an actual dynamic system by using online measurements of the state trajectory. The algorithm is shown to be extremely robust to mismatch between the model and the system. It is a projected gradient method that uses the measured terminal state error of the actual system and gradients based on the theoretical state equation of the system but evaluated along the actual state trajectory. The success of the method is demonstrated on an under actuated double pendulum system called the acrobot

Keywords

adaptive control; conjugate gradient methods; intelligent control; learning (artificial intelligence); optimal control; robust control; acrobot; dynamic system; intelligent control; measured terminal state error; minimum time trajectory learning; mismatch robustness; online measurements; projected gradient method; state equation; state trajectory; under-actuated double pendulum system; Equations; Gradient methods; History; Mechanical engineering; Mechanical variables measurement; Performance analysis; Robustness; Sensor systems; State-space methods; Time measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, Proceedings of the 1995

Conference_Location

Seattle, WA

Print_ISBN

0-7803-2445-5

Type

conf

DOI

10.1109/ACC.1995.520970

Filename

520970