Browsing by Author "Cao, Yi"

Browsing by Author "Cao, Yi"

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  • 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 ...
  • Nonlinear system identification for predictive control using continuous time recurrent neural networks and automatic differentiation. 
    Al Seyab, Rihab Khalid Shakir; Cao, Yi (Elsevier Science B.V., Amsterdam., 2008-07-01)
    In this paper, a continuous time recurrent neural network (CTRNN) is developed to be used in nonlinear model predictive control (NMPC) context. The neural network represented in a general nonlinear state-space form is ...
  • Optimal Design and Operation of Heat Exchanger Network 
    Salihu, Adamu Girei (Cranfield University, 2015-08)
    Heat exchanger networks (HENs) are the backbone of heat integration due to their ability in energy and environmental managements. This thesis deals with two issues on HENs. The first concerns with designing of economically ...
  • Optimization of petroleum reservoir waterflooding using receding horizon approach 
    Grema, Alhaji Shehu; Cao, Yi (IEEE, 2013-07-25)
    In this paper, static and dynamic optimization of a reservoir waterflooding process for enhanced oil recovery was studied. The dynamic optimization was achieved using receding horizon (RH) algorithms. Two forms of RH which ...
  • Optimization of Reservoir Waterflooding 
    Grema, Alhaji Shehu (Cranfield University, 2014-10)
    Waterflooding is a common type of oil recovery techniques where water is pumped into the reservoir for increased productivity. Reservoir states change with time, as such, different injection and production settings will ...
  • Petroleum refinery scheduling with consideration for uncertainty 
    Hamisu, Aminu Alhaji (Cranfield University, 2015-07)
    Scheduling refinery operation promises a big cut in logistics cost, maximizes efficiency, organizes allocation of material and resources, and ensures that production meets targets set by planning team. Obtaining accurate ...
  • Prediction of Convergence Dynamics of Design Performance using Differential Recurrent Neural Networks 
    Cao, Yi; Jin, Yaochu; Kowalczykiewicz, Michal; Sendhoff, Bernhard (2008-12-31)
    Computational Fluid Dynamics (CFD) simulations have been extensively used in many aerodynamic design optimization problems, such as wing and turbine blade shape design optimization. However, it normally takes very long ...
  • Predictive condition monitoring of industrial systems for improved maintenance and operation 
    Ruiz Cárcel, Cristóbal (Cranfield University, 2014-07)
    Maintenance strategies based on condition monitoring of the different machines and devices in an industrial process can minimize downtime, increase the safety of plant operations and help in the process of decision-taking ...
  • Predictive control for the ALSTOM gasifier problem. 
    Seyab, R. K. A.; Cao, Yi; Yang, Shuang-Hua (Institution of Electrical Engineers, 2006-05-09)
    Model predictive control (MPC) has become the first choice of control strategy in many cases especially in the process industry because it is intuitive and can explicitly handle MIMO (multiple input multiple output) ...
  • Receding horizon control for oil reservoir waterflooding process 
    Grema, Alhaji Shehu; Cao, Yi (Taylor and Francis, 2017-10-02)
    Waterflooding is a recovery technique where water is pumped into an oil reservoir for increase in production. Changing reservoir states will require different injection and production settings for optimal operation which ...
  • Retrofit self-optimizing control of Tennessee Eastman process 
    Ye, Lingjian; Cao, Yi; Yuan, Xiaofeng; Song, Zhihuan (Institute of Electrical and Electronics Engineers, 2016-05-19)
    This paper considers near-optimal operation of the Tennessee Eastman (TE) process by using a retrofit self-optimizing control (SOC) approach. Motivated by the factor that most chemical plants in operation have already been ...
  • Retrofit self-optimizing control: a step forward towards real implementation 
    Ye, L.; Cao, Yi; Yuan, X.; Song, Z. (Institute of Electrical and Electronics Engineers (IEEE), 2017-02-14)
    After 15 year development, it is still hard to find any real application of the self-optimizing control (SOC) strategy, although it can achieve optimal or near optimal operation in industrial processes without repetitive ...
  • A review of kernel methods for feature extraction in nonlinear process monitoring 
    Pilario, Karl Ezra; Shafiee, Mahmood; Cao, Yi; Lao, Liyun; Yang, Shuang-Hua (MDPI, 2019-12-23)
    Kernel methods are a class of learning machines for the fast recognition of nonlinear patterns in any data set. In this paper, the applications of kernel methods for feature extraction in industrial process monitoring are ...