Cubic-RBF-ARX modeling and model-based optimal setting control in head and tail stages of cut tobacco drying process

This paper presents a data-driven modeling technique used to build a multi-sampling-rate RBF-ARX (MSR-RBF-ARX) model for capturing and quantifying global nonlinear characteristics of the head and tail stage drying process of a cylinder-type cut tobacco drier. In order to take full account of influence of the input variables to outlet cut tobacco moisture content in whole drying process, and meanwhile, to avoid orders of the model too large, this paper designs a special MSR-RBF-ARX model structure that incorporates the advantages of parametric model and nonparametric model in nonlinear dynamics description for the process. Considering this industrial process identification problem, a hybrid optimization algorithm is proposed to identify the MSR-RBF-ARX model using the multi-segment historical data set in different seasons and working conditions. To obtain better long-term forecasting performance of the model, a long-term forecasting performance index is introduced in the algorithm. To accelerate the computational convergence, in the hybrid algorithm, one-step predictive errors of the model are minimized first to get a set of the model parameters that are just used as the model initial parameters, and then, the model parameters are further optimized by minimizing long-term forecasting errors of the model. Based on the estimated model, a set of optimal setting curves of the input variables are obtained by optimizing parameters of the designed input variable models. The effectiveness of the proposed modeling and setting control strategy for the process are demonstrated by simulation studies

Indoor air Quality and Its Effects on Health in Urban Houses of Indonesia: A case study of Surabaya

There is a possibility that the sick building syndrome has already spread widely among the newly constructed apartments in major cities of Indonesia. This study investigates the current conditions of indoor air quality, focusing especially on formaldehyde and TVOC, and their effects on health among occupants in the urban houses located in the city of Surabaya. A total of 471 respondents were interviewed and 82 rooms were measured from September 2017 to January 2018. The results indicated that around 50% of the respondents in the apartments showed some degrees of chemical sensitivity risk. More than 60% of the measured formaldehyde levels in the apartments exceeded the WHO standard, 0.08 ppm. The respondents living in rooms with higher mean formaldehyde values tended to have higher multiple chemical sensitivity risk scores. KEYWORDS: Indoor air quality, Sick building syndrome, QEESI, Formaldehyde, Developing countrie