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Optimal Control Strategy for Automated People Mover System using Robust H∞ Integral-Backstepping MIMO PID Controller

Endra Joelianto, Lucas E. Suryana, Augie Widyotriatmo, Yosi A. Hidayat


Automatic people mover (APM) system is a small-scale automated guided transportation system used for small areas. Using communications-based train control (CBTC) signalling technology, APM can be operated automatically through automatic train operation (ATO) accomplished by providing a speed profile as a reference value to be tracked by the APM. Modern urban passenger trains employ ATO to control the train speed within its speed limits. Moreover, APM is required to stop and start at stations, and to indicate the stopping position for the train after the automatic train protection (ATP) has confirmed that the line is empty. The ATO system will perform these parts of the operation with the exception of the driver normally starting the train. In the paper, speed profiles are formulated for every trip between stations by considering the travel time and speed of the train, and obtained using Interior Point Method (IPM) in dynamics optimization. The resulted speed limit, acceleration limit, and distance become the limitations of the system. The optimal speed profile is designed using minimal time objective functions and then employed as the optimal reference value aimed at the control system of the ATO formulated with the robust H∞ integral-backstepping proportional-integral-derivative (PID) controller. The robust approach is solved by means of full-state feedback in regard to augmented state space representation of the APM dynamical system to handle uncertainties caused by mass variations from the number of passengers in the train system.


Dynamic optimization; Interior Point Method (IPM); Automatic Train Operation (ATO); Uncertainty; Robust H∞ Integral-Backstepping; MIMO PID Controller.

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