298 P. Garg et al. Fig. 36.9 Train velocity control using node 3 for LQI implementation Fig. 36.10 Plot of node displacements for a closed loop system implemented with LQI optimization 36.6 Future Work As mentioned earlier, in this paper I had assumed a static displacement problem by considering a very long train, already over the bridge and the cars have a constant weight exerting a constant force on the bridge. The next step in this project will be implementation of a time varying system, using a moving load, which will have no initial displacement and as the load passes over the bridge, the displacement will change. As soon as it exceeds the threshold value, the LQR will try to reduce the speed accordingly. This system will then be developed further by cascading with dynamic train model which will interact with the bridge dynamics, simulating a moving mass system. The final model will have LQR optimization to control the train speed and bridge displacement in real time in practical environment.
RkJQdWJsaXNoZXIy MTMzNzEzMQ==