000020318 001__ 20318
000020318 005__ 20170118182409.0
000020318 04107 $$aeng
000020318 046__ $$k2017-01-09
000020318 100__ $$aChoutri, Kheireddine
000020318 24500 $$aDevelopment of An Auxiliary Offline Controller Based on Neural Network for a Shaking Table With An Online Pid Control System

000020318 24630 $$n16.$$pProceedings of the 16th World Conference on Earthquake Engineering
000020318 260__ $$b
000020318 506__ $$arestricted
000020318 520__ $$2eng$$aThe shaking table is a powerful tool in dynamic testing in which a high signal reproduction fidelity is considered as a distinguishing feature of the system. However, a precise control of the platform motions to ensure desired accelerations is still a challenging target because of the interference of the different mechanical, hydraulic and electronic parts as well as the test specimen particularly their strong inherent nonlinearities. This study addresses the improvement of acceleration signal matching on a shaking table using an additional online controller based on a recurrent neural network algorithm. The latter is developed to provide an additional correction to the command signal produced by the actual shaking table control system, in order to reduce the signal distortion between the reproduced signal and the desired one. The shaking table is simulated by its transfer function implemented in Matlab/Simulink, including a PID online controller. The training of the Neural Network is performed offline. The response of the transfer function of the system acceleration is used as input to the NN. The desired signal in acceleration represents the NN target. After training, the NN is implemented in Matlab/Simulink model in order to provide an online correction to the output signal, in the same time as the PID. To evaluate the performance of the proposed control scheme i.e a PID-NN controller, a correlation coefficient R has been calculated between the target signal and the system output. Results show that the NN controller improves the signal matching in acceleration.

000020318 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000020318 653__ $$aShaking table; Neural Network; Elman Neural Network; control; online controller.

000020318 7112_ $$a16th World Conference on Earthquake Engineering$$cSantiago (CL)$$d2017-01-09 / 2017-01-13$$gWCEE16
000020318 720__ $$aChoutri, Kheireddine$$iLarbi, Selma$$iBourahla, Nouredine$$iBenchoubane, Hacine
000020318 8560_ $$ffischerc@itam.cas.cz
000020318 8564_ $$s279161$$uhttps://invenio.itam.cas.cz/record/20318/files/975.pdf$$yOriginal version of the author's contribution as presented on USB, paper 975.
000020318 962__ $$r16048
000020318 980__ $$aPAPER