This paper presents the online optimal control strategies for multiple-chiller plants in large buildings with enhanced robustness and cost efficiency, including optimization of chilled water supply temperature set-point, chiller sequencing control, optimal start control and electrical demand limiting control. The chilled water supply temperature set-point optimization aims to minimize the total energy consumption of chillers and chilled water distribution pumps. In the chiller sequencing control, three schemes are used to enhance its control robustness, including a data fusion scheme for improved reliability of building cooling load measurement, a simplified adaptive model of maximum chiller cooling capacity, and an online sensor fault detection and diagnosis(FDD). In the chiller optimal start control, a model-based strategy is proposed for minimizing the energy consumption in the morning start period. The model-based optimal start control strategy considers both the recovery ability and the pre-cooling lead time as its optimizing variables. The peak demand limiting control strategy minimizes the monthly electricity bill by predicting a suitable monthly peak demand threshold and restraining the daily peak demand to the threshold. These control strategies are validated using the dynamic simulation of the central chiller plant in a high-rising building in Hong Kong. © All Rights Reserved.