Abstract
In this paper, an extended state space predictive control (ESSPC) strategy has been applied to gas turbine in combined cycle power plant. This proposed predictive control needn’t solve Diophantine equation online. In addition, in order to overcome the shortcoming of the conventional state space predictive control (SSPC) which only takes output errors into consideration, the objective function of ESSPC includes both output errors and the variation of the system states. In the rolling optimization part, the quadratic program (QP) method is applied to deal with the limitations on the inputs of system. Simulation results show that the proposed algorithm has better tracking ability and stability compared with conventional state space predictive controller in the same condition.
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Acknowledgments
This work is supported by the National Science Foundation of China (61374052, 61511130082) and the Fundamental Research Funds for the Central Universities 2016ZZD03.
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Hou, G., Wang, T., Du, H., Zhang, J., Zheng, X. (2017). Extended State Space Predictive Control of Gas Turbine System in Combined Cycle Power Plant. In: Li, K., Xue, Y., Cui, S., Niu, Q., Yang, Z., Luk, P. (eds) Advanced Computational Methods in Energy, Power, Electric Vehicles, and Their Integration. ICSEE LSMS 2017 2017. Communications in Computer and Information Science, vol 763. Springer, Singapore. https://doi.org/10.1007/978-981-10-6364-0_42
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DOI: https://doi.org/10.1007/978-981-10-6364-0_42
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