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Up a levelAbbas, Faisal and Saleem, Omer and Wang, Lijuan and Yan, Yong (2024) A self-adaptive fractional-order PID controller for the particle velocity regulation in a pneumatic conveying system. Transactions of the Institute of Measurement and Control. pp. 1-13. ISSN 0142-3312
Liu, Yefeng and Zhang, Qichun and Yue, Hong (2021) Stochastic distribution tracking control for stochastic non-linear systems via probability density function vectorisation. Transactions of the Institute of Measurement and Control, 43 (14). pp. 3149-3157. ISSN 0142-3312
Gao, Ke and Song, Jia and Yang, Erfu (2019) Stability analysis of the high-order extended state observers for a class of nonlinear control systems. Transactions of the Institute of Measurement and Control, 41 (15). pp. 4370-4379. ISSN 0142-3312
Alkaya, Alkan and Grimble, Michael John (2015) Non-linear minimum variance estimation for fault detection systems. Transactions of the Institute of Measurement and Control, 37 (6). pp. 805-812. ISSN 0142-3312
Sun, Xubin and Yue, Hong and Wang, Hong (2006) Modelling and control of the flame temperature distribution using probability density function shaping. Transactions of the Institute of Measurement and Control, 28 (5). pp. 401-428. ISSN 0142-3312
Sanchez, A. and Wade, M.J. and Katebi, M.R. (2005) A software platform for real-time control and monitoring of a wastewater treatment plant. Transactions of the Institute of Measurement and Control, 27 (3). pp. 153-172. ISSN 0142-3312
Wade, M.J. and Sanchez, A. and Katebi, M.R. (2005) On realtime control and process monitoring of wastewater treatment plants: realtime process monitoring. Transactions of the Institute of Measurement and Control, 27 (3). pp. 173-193. ISSN 0142-3312
Grimble, M.J. (2003) Performance assessment and benchmarking LQG predictive optimal controllers for discrete. Transactions of the Institute of Measurement and Control, 25 (3). pp. 239-264. ISSN 0142-3312
Wang, H. and Yue, H. (2003) A rational spline model approximation and control of output probability density functions for dynamic stochastic systems. Transactions of the Institute of Measurement and Control, 25 (2). pp. 93-105.