A parallel neuro-controller for DC motors containing nonlinear friction

“…The DC motor is an essential source of movement in electromechanical systems which are not too powerful [2]. Its main advantage is that it is easy to control the speed or position with a wide adjustable range in order to follow a predetermined time trajectory under different load inputs [3]. Extensive research efforts have been carried out in the past, and various applications can be found in literature: Applications include robot manipulators [4], positioning tables [5], liquid pumps [6], overhead crane mechanisms [7] or disk motion control [8], among many others.…”

Section: Introductionmentioning

confidence: 99%

Control of a DC motor using algebraic derivative estimation with real time experiments

2014

View full text Add to dashboard Cite

This paper presents an experimental control scheme for DC motors which combines an overlapping implementation of the algebraic derivative estimation method and a disturbance estimator based on the aforementioned algebraic derivative method. The methodol-ogy only requires the measurement of the angular position of the motor and the voltage input to the motor. The main advantages of the proposed approach are: it is independent of the motor's initial conditions, the methodology is robust to Coulomb friction effects, it does not require any statistical knowledge of the noises that corrupt the data, the deriva-tive estimation process does not require initial conditions or dependence between the sys-tem input and output, and the algorithm is computed online and in real time. The effectiveness of the proposed controller has been verified by means of computer simula-tions and it has also been experimentally implemented on a laboratory prototype with excellent results in both, stabilization and trajectory tracking tasks.

show abstract

A parallel neuro-controller for DC motors containing nonlinear friction

Cited by 74 publications

References 17 publications

Second-order sliding mode control with experimental application

Second-order sliding mode control with experimental application

Variance sensitive adaptive threshold-based PCA method for fault detection with experimental application

Control of a DC motor using algebraic derivative estimation with real time experiments

Contact Info

Product

Resources

About