Technical paper: Yucai Zhu, Chao Yang, Xi Chen, Jinming Zhou and Jun Zhao (2022). Identification-based real-time optimization and its application to power plants. Control Engineering Practice, Vol. 123, pp. 1-16.
Tai-Ji RTO® is a real-time optimizer for multivariable industrial processes, boosting yield, saving energy, cutting raw-material use, and reducing emissions. The optimization formulation covers decision variables, operating points, objective functions, dynamic models and model error bounds. Tai-Ji RTO® automatically performs online identification tests to identify optimization gradients and compute iteration step sizes.
Traditional RTO methods relies on first-principles models that are costly to develop and to maintain, and last and most, they have large model errors. These difficulties hinders real life industrial applications. Tai-Ji RTO® uses system identification to obtain accurate gradient estimates at low cost, greatly improving feasibility in industrial applications.
