Application-oriented input design for room occupancy estimation algorithms
暂无分享,去创建一个
Karl Henrik Johansson | Afrooz Ebadat | Giulio Bottegal | Damiano Varagnolo | Bo Wahlberg | B. Wahlberg | Giulio Bottegal | K. Johansson | A. Ebadat | Damiano Varagnolo
[1] P. Caines,et al. Asymptotic normality of prediction error estimators for approximate system models , 1980 .
[2] D.G. Dudley,et al. Dynamic system identification experiment design and data analysis , 1979, Proceedings of the IEEE.
[3] Håkan Hjalmarsson,et al. Chance constrained input design , 2011, IEEE Conference on Decision and Control and European Control Conference.
[4] Valenzuela Pacheco,et al. On risk-coherent input design and Bayesian methods for nonlinear system identification , 2016 .
[5] Tuan Anh Nguyen,et al. Energy intelligent buildings based on user activity: A survey , 2013 .
[6] Giuseppe Carlo Calafiore,et al. The scenario approach to robust control design , 2006, IEEE Transactions on Automatic Control.
[7] Cristian R. Rojas,et al. MPC Oriented Experiment Design , 2011 .
[8] Afrooz Ebadat,et al. Regularized Deconvolution-Based Approaches for Estimating Room Occupancies , 2015, IEEE Transactions on Automation Science and Engineering.
[9] W Wim Zeiler,et al. Occupancy measurement in commercial office buildings for demand-driven control applications : a survey and detection system evaluation , 2015 .
[10] Xavier Bombois,et al. Least costly identification experiment for control , 2006, Autom..
[11] Alex Simpkins,et al. System Identification: Theory for the User, 2nd Edition (Ljung, L.; 1999) [On the Shelf] , 2012, IEEE Robotics & Automation Magazine.
[12] Jian Zhang,et al. Review of Literature on Terminal Box Control, Occupancy Sensing Technology and Multi-zone Demand Control Ventilation (DCV) , 2012 .
[13] Silvia Santini,et al. Occupancy Detection from Electricity Consumption Data , 2013, BuildSys@SenSys.
[14] Robert X. Gao,et al. Occupancy estimation for smart buildings by an auto-regressive hidden Markov model , 2014, 2014 American Control Conference.
[15] Jan-Olof Dalenbäck,et al. CO2 sensors for occupancy estimations: Potential in building automation applications , 2014 .
[16] Håkan Hjalmarsson,et al. From experiment design to closed-loop control , 2005, Autom..
[17] Rita Streblow,et al. CO2 based occupancy detection algorithm: Experimental analysis and validation for office and residential buildings , 2015 .
[18] Zheng Yang,et al. A Non-Intrusive Occupancy Monitoring System for Demand Driven HVAC Operations , 2012 .
[19] Håkan Hjalmarsson,et al. System identification of complex and structured systems , 2009, 2009 European Control Conference (ECC).
[20] Rui Zhang,et al. Occupancy detection through an extensive environmental sensor network in an open-plan office building , 2009 .
[21] Håkan Hjalmarsson,et al. Identification of ARX systems with non-stationary inputs - asymptotic analysis with application to adaptive input design , 2009, Autom..
[22] Heshmat A. Aglan. Predictive model for CO2 generation and decay in building envelopes , 2003 .
[23] Graham C. Goodwin,et al. Robust optimal experiment design for system identification , 2007, Autom..
[24] Karl Henrik Johansson,et al. Multi-room occupancy estimation through adaptive gray-box models , 2015, 2015 54th IEEE Conference on Decision and Control (CDC).
[25] Lennart Ljung,et al. System Identification: Theory for the User , 1987 .
[26] Bo Wahlberg,et al. On optimal input design in system identification for control , 2010, 49th IEEE Conference on Decision and Control (CDC).
[27] Jirí Cigler,et al. Dual control approach for zone model predictive control , 2013, 2013 European Control Conference (ECC).
[28] Shengwei Wang,et al. Experimental Validation of CO2-Based Occupancy Detection for Demand-Controlled Ventilation , 1999 .
[29] Sean P. Meyn,et al. A sensor-utility-network method for estimation of occupancy in buildings , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.
[30] Luis M. Candanedo,et al. Accurate occupancy detection of an office room from light, temperature, humidity and CO2 measurements using statistical learning models , 2016 .
[31] Rui Zhang,et al. An information technology enabled sustainability test-bed (ITEST) for occupancy detection through an environmental sensing network , 2010 .
[32] Manfred Morari,et al. Importance of Long-Term Occupancy Information - A Validation with Real Occupancy Data , 2013 .
[33] Luca P. Carloni,et al. An experimental investigation of occupancy-based energy-efficient control of commercial building indoor climate , 2014, 53rd IEEE Conference on Decision and Control.