Browsing by Author "Cao, Yi"

Browsing by Author "Cao, Yi"

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  • Identification and predictive control of a multistage evaporator 
    Atuonwu, J. C.; Cao, Yi; Rangaiah, G. P.; Tade, M. O. (Elsevier Science B.V., Amsterdam., 2010-12-31)
    A recurrent neural network-based nonlinear model predictive control (NMPC) scheme in parallel with PI control loops is developed for a simulation model of an industrial-scale five-stage evaporator. Input-output data from ...
  • Identification of discrete-time output error model for industrial processes with time delay subject to load disturbance 
    Dong, Shijian; Liu, Tao; Wang, Wei; Bao, Jie; Cao, Yi (Elsevier, 2016-12-22)
    In this paper, a bias-eliminated output error model identification method is proposed for industrial processes with time delay subject to unknown load disturbance with deterministic dynamics. By viewing the output response ...
  • Identification of gas-liquid flow regimes using a non-intrusive Doppler ultrasonic sensor and virtual flow regime maps 
    Nnabuife, Godfrey; Pilario, Karl Ezra; Lao, Liyun; Cao, Yi; Shafiee, Mahmood (Elsevier, 2019-05-17)
    The accurate prediction of flow regimes is vital for the analysis of behaviour and operation of gas/liquid two-phase systems in industrial processes. This paper investigates the feasibility of a non-radioactive and ...
  • Improved branch and bound method for control structure screening 
    Cao, Yi; Saha, Prabirkumar (Elsevier Science B.V., Amsterdam., 2005-03-01)
    The main aim of this paper is to present an improved algorithm of “Branch and Bound” method for control structure screening. The new algorithm uses a best- first search approach, which is more efficient than other algorithms ...
  • Incorporating feedforward action into self-optimising control policies 
    Umar, Lia Maisarah; Cao, Yi; Kariwala, Vinay (Chemical Institute of Canada, 2014-01-31)
    Control structure design traditionally involves two steps of selections, namely the selection of controlled and manipulated variables and the selection of pairings interconnecting these variables. The available criteria ...
  • A kernel design approach to improve kernel subspace identification 
    Salgado Pilario, Karl Ezra; Cao, Yi; Shafiee, Mahmood (IEEE, 2020-05-27)
    Subspace identification methods, such as canonical variate analysis (CVA), are non-iterative tools suitable for the state-space modelling of multi-input, multi-output (MIMO) processes, e.g. industrial processes, using ...
  • Mixed kernel canonical variate dissimilarity analysis for incipient fault monitoring in nonlinear dynamic processes 
    Pilario, Karl Ezra; Cao, Yi; Shafiee, Mahmood (Elsevier, 2018-12-25)
    Incipient fault monitoring is becoming very important in large industrial plants, as the early detection of incipient faults can help avoid major plant failures. Recently, Canonical Variate Dissimilarity Analysis (CVDA) ...
  • Multi-layer contribution propagation analysis for fault diagnosis 
    Tan, Ruomu; Cao, Yi (Springer, 2018-09-27)
    The recent development of feature extraction algorithms with multiple layers in machine learning and pattern recognition has inspired many applications in multivariate statistical process monitoring. In this work, two ...
  • Multiobjective Optimisation of Restricted Complexity Controllers 
    Cao, Yi; Yan, Wenjun (Lavoisier, 2003-01-01)
    Restricted complexity controller design for the active suspension benchmark problem call for papers EJC special issue on Design and Optimisation of Restricted Complexity Controllers. Web site http:/www-ejc.ensieg. inpg.fr/, ...
  • Multiobjective process controllability analysis 
    Cao, Yi; Yang, Zhijia (Elsevier Science B.V., Amsterdam., 2004-01-15)
    A new approach for process controllability analysis by using multiobjective optimisation techniques is proposed. Within the approach, a set of performance specifications, such as minimum control error and input effort with ...
  • Multiphase flow instability and active slug control solutions 
    Tandoh, Henry Kwaw Ayisi (2018-03)
    Slugging as a flow assurance challenge is an upsetting condition to the oil and gas industry due to the instabilities it poses on the system. The negative repercussions associated with slug flow stems from the inlet through ...
  • Multiphase severe slug flow control 
    Ogazi, Anayo Isaac (Cranfield University, 2011-01)
    Severe slug flow is one of the most undesired multiphase flow regimes, due to the associated instability, which imposes major challenges to flow assurance in the oil and gas industry. This thesis presents a comprehensive ...
  • Networked control systems and wireless sensor networks: theories and applications. 
    Yang, Shuang-Hua; Cao, Yi (Taylor & Francis, 2008-11-01)
    Abstract This special issue aims to provide innovative research work that has recently been carried out in networked control and wireless sensor networks, including both theoretical developments, experimental and/or ...
  • Neural predictive control of broiler chicken and pig growth 
    Demmers, Theo G. M.; Cao, Yi; Gauss, Sophie; Lowe, John C.; Parsons, David J.; Wathes, Christopher M. (Elsevier, 2018-07-20)
    Active control of the growth of broiler chickens and pigs has potential benefits for farmers in terms of improved production efficiency, as well as for animal welfare in terms of improved leg health in broiler chickens. ...
  • Neural predictive control of broiler chicken growth 
    Demmers, Theo G. M.; Cao, Yi; Gauss, Sophie; Lowe, John C.; Parsons, David J.; Wathes, Christopher M. (Elsevier, 2010-12-31)
    Active control of the growth of broiler chickens has potential benefits for farmers in terms of improved production efficiency, as well as for animal welfare in terms of improved leg health. In this work, a differential ...
  • Nonlinear Dynamic Process Monitoring Using Canonical Variate Analysis and Kernel Density Estimations 
    Odiowei, P. P.; Cao, Yi (IEEE, 2010-02-05)
    The Principal Component Analysis (PCA) and the Partial Least Squares (PLS) are two commonly used techniques for process monitoring. Both PCA and PLS assume that the data to be analysed are not self-correlated i.e. ...
  • Nonlinear dynamic process monitoring using kernel methods 
    Samuel, Raphael Tari (Cranfield University, 2016-08)
    The application of kernel methods in process monitoring is well established. How- ever, there is need to extend existing techniques using novel implementation strate- gies in order to improve process monitoring performance. ...
  • Nonlinear model predictive control for the ALSTOM gasifier. 
    Al Seyab, Rihab Khalid Shakir; Cao, Yi (Elsevier Science B.V., Amsterdam., 2006-09-01)
    In this work a nonlinear model predictive control based on Wiener model has been developed and used to control the ALSTOM gasifier. The 0% load condition was identified as the most difficult case to control among three ...
  • Nonlinear model predictive control using automatic differentiation 
    Al Seyab, Rihab Khalid Shakir (Cranfield University, 2006)
    Although nonlinear model predictive control (NMPC) might be the best choice for a nonlinear plant, it is still not widely used. This is mainly due to the computational burden associated with solving online a set of ...
  • Nonlinear process fault detection and identification using kernel PCA and kernel density estimation 
    Samuel, Raphael; Cao, Yi (Taylor & Francis, 2016-08-28)
    Kernel principal component analysis (KPCA) is an effective and efficient technique for monitoring nonlinear processes. However, associating it with upper control limits (UCLs) based on the Gaussian distribution can deteriorate ...