Optimization Control of DC Motor with Linear Quadratic Regulator and Genetic Algorithm Approach

Abstract

This paper presents LQR and GA controllers which applied to control the speed of a DC
motor and to maintain the rotation of the motor shaft with particular step response. In
the state space, the control strategy is the states feedback and the most used techniques
are the LQR. Liner quadratic regulator (LQR) provides an optimal control law for a
linear system. It’s a control strategy based on minimizing a quadratic performance
index. In despite of the good results obtained from these method, the control design is
not a straight forward task due to the trial and error method involved in the definition of
weight matrices. In such cases, may be hard tuning the controller parameters in order to
obtain the optimal behavior of the system. In this work, it proposes a states feedback
technique in which there are no trial and error processes involved and the control design
is carried out to fulfill specifications, for minimize overshoot and minimize settling and
rising times. The proposed technique is based on the use a genetic algorithms. The
obtained results show that is possible to design controllers which fulfill design
specifications.