Adaptive dual control with online outlier detection for uncertain systems. (October 2022) - Ma, Xuehui; Qian, Fucai; Zhang, Shiliang; Wu, Li; Liu, Lei
Abstract: This paper proposes an adaptive dual control with outlier detection that is robust to the occurrence of outliers in uncertain systems. Outliers occasionally exist in system process noise and observation noise, which could cause poor parameter estimation and degraded control performance of uncertain systems. For this reason, we devise an online outlier detection mechanism to filter the outliers so as to enhance the parameter estimation of uncertain systems. The devised mechanism makes decisions on outlier detection via the generated predicted regions where the newly arriving data is expected to locate, and the predicted regions are updated in real-time according to the historical data. The detection mechanism is integrated into the design of adaptive dual control, which is derived based on the bicriterial method. Compared with classical dual control merely considering uncertainty in input and output data stream, we are the first to include the uncontrollable excitations into the structure of dual control to fit practical scenarios, and this inclusion also provides an extensive cover on outliers to be detected. The improved performance of the proposed approach is verified using a mathematical model through one-time simulation and Monte Carlo simulations under different conditions, and we also evaluate our method in the control of fermentation sterilization process for more convincing results. Highlights: An adaptive dual control with online outlier detection is proposed, which is robust to the occurrence of outliers in uncertain systems. The proposed outlier detection mechanism includes both distance and direction criterion for the decision-making of outlier detection. Uncontrollable excitations are firstly added into the structure of bicriterial method based adaptive dual control to fit practical scenarios. The improved performance of the proposed method is verified in the mathematical model and fermentation sterilization control process.