15th EUROPT Workshop on Advances in Continuous Optimization

Montréal, Canada, 12 — 14 juillet 2017

15th EUROPT Workshop on Advances in Continuous Optimization

Montréal, Canada, 12 — 14 juillet 2017

Horaire Auteurs Mon horaire
Cal add eabad1550a3cf3ed9646c36511a21a854fcb401e3247c61aefa77286b00fe402

Dynamic Control and Optimization with Applications II

13 juil. 2017 11h30 – 12h45

Salle: Saine Marketing

Présidée par Sebti Kerbal

3 présentations

  • Cal add eabad1550a3cf3ed9646c36511a21a854fcb401e3247c61aefa77286b00fe402
    11h30 - 11h55

    Robust real-time optimization for blending operation of alumina production

    • Kok Lay TEO, prés., Curtin University

    The blending operation is a key process in alumina production. The real-time optimization (RTO) of finding an optimal raw material propor- tioning is crucially important for achieving the desired quality of the product. However, the presence of uncertainty is unavoidable in a real process, lead- ing to much difficulty for making decision in real-time. This paper presents a novel robust real-time optimization (RRTO) method for alumina blending operation, where no prior knowledge of uncertainties is needed to be utilized. The robust solution obtained is applied to the real plant and the two-stage operation is repeated. When compared with the previous intelligent optimiza- tion (IRTO) method, the proposed two-stage optimization method can better address the uncertainty nature of the real plant and the computational cost is much lower. From practical industrial experiments, the results obtained show that the proposed optimization method can guarantee that the desired quality of the product quality is achieved in the presence of uncertainty on the plant behavior and the qualities of the raw materials. This outcome suggests that the proposed two-stage optimization method is a practically significant approach for the control of alumina blending operation.

  • Cal add eabad1550a3cf3ed9646c36511a21a854fcb401e3247c61aefa77286b00fe402
    11h55 - 12h20

    Optimal Path Finding in Urban Operations

    • Yu Hongjun, The University of Adelaide
    • Cheng-Chew Lim, prés., The University of Adelaide
    • Shi Peng, The University of Adelaide

    Emergencies operations can occur in confined urban buildings. Urban operation units often encounter mobile and static obstacles, and must find in real time the optimal path to handle such complicated environment. This presentation gives an agent-based path-finding algorithm for real-time realization. Reducing repetitive computation is achieved by classifying the obstacles into clusters. Agent-based classifiers allow parallel computing to improve operation units’ response. Consensus among multiple obstacle perspectives can lead to an exhaustive set of all possible clusters. The problem is addressed by introducing probability-triggering conditions to a dynamic programming approach to find the desired paths in a confined area.

  • Cal add eabad1550a3cf3ed9646c36511a21a854fcb401e3247c61aefa77286b00fe402
    12h20 - 12h45

    Event-Triggered Hybrid Consensus for Multi-Agent Networks With Directed Topologies

    • Honglei Xu, prés., Curtin University

    This paper will introduce an event-triggered hybrid control technique for the multi-agent network consensus problem with directed topologies and pull-based setup. The hybrid controller consists of an event-triggered feedback controller and an impulsive state update rule. The feedback control renews agents' feedback information at the event times and the impulsive control rule updates those agents' system states at the impulsive times. We first derive general event-triggered hybrid principles. The results are hence reduced to synchronous hybrid principles, where all impulsive times coincide with the event times. Numerical examples provide evidences that the hybrid control strategy can exhibit a better convergence performance than pure event-triggered control.