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J. B. Gomm
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2020 – today
- 2023
- [c16]Azizeh Lotfivand, Dingli Yu
, Barry Gomm:
State of Charge Estimation Using Unscented Kalman Filter in Electric Vehicles. ICAC 2023: 1-5 - 2022
- [c15]Azizeh Lotfivand, Dingli Yu
State Of Charge estimation using Extended Kalman Filter in Electric Vehicles. ICAC 2022: 1-5 - [c14]Kingsley Madubuike, Cliff Mayhew, Qian Zhang, J. Barry Gomm, Ding-Li Yu
Fault tolerant control and fault diagnosis of a variable speed pitch angle hydraulic system. ICAC 2022: 1-6 - 2020
- [j14]Haiying Qi, Yiran Shi, Shoutao Li, Yantao Tian, Ding-Li Yu
Fault tolerant control for nonlinear systems using sliding mode and adaptive neural network estimator. Soft Comput. 24(15): 11535-11544 (2020)
2010 – 2019
- 2019
- [c13]Kingsley Madubuike, Cliff Mayhew, Qian Zhang
Fault diagnosis for wind turbine systems using a neural network estimator. ICAC 2019: 1-7 - [c12]Kingsley Madubuike, Cliff Mayhew, Qian Zhang
Fault diagnosis for wind turbine systems using unknown input observer. ICAC 2019: 1-6 - 2018
- [c11]Haiying Qi, Abdelkarim M. Ertiame, Kingsley Madubuike, Ding-Li Yu
Nonlinear Observer Fault Detection for a Multivariable Process Using a Learning Methodology. ICAC 2018: 1-6 - [c10]Haiying Qi, Abdelkarim M. Ertiame, Kingsley Madubuike, Ding-Li Yu
Failure Prediction for an Exothermic Semi-batch Reactor via A combined EKF with Statistical Method. ICAC 2018: 1-6 - 2017
- [j13]Wael Alharbi
Genetic Algorithm Optimisation of PID Controllers for a Multivariable Process. Int. J. Recent Contributions Eng. Sci. IT 5(1): 77-96 (2017) - 2016
- [j12]Kumaran Rajarathinam, J. Barry Gomm, Ding-Li Yu
PID controller tuning for a multivariable glass furnace process by genetic algorithm. Int. J. Autom. Comput. 13(1): 64-72 (2016) - [c9]Kumaran Rajarathinam, J. Barry Gomm, Dingli Yu
Model parameters identification for excess oxygen by Standard Genetic Algorithm. ICAC 2016: 198-203 - 2015
- [c8]Kumaran Rajarathianm, J. Barry Gomm, Karl O. Jones
Predetermined time constant approximation method for optimising search space boundary by standard genetic algorithm. CompSysTech 2015: 38-45 - [c7]Kumaran Rajarathinam, J. Barry Gomm, Dingli Yu
An improved search space resizing method for model identification by Standard Genetic Algorithm. ICAC 2015: 1-6 - 2014
- [c6]Kumaran Rajarathianm, J. Barry Gomm, Karl O. Jones
Decentralised control optimisation for a glass furnace by SGAs. CompSysTech 2014: 248-255 - [c5]Kumaran Rajarathinam, J. Barry Gomm, Dingli Yu
Decentralised PID control tuning for a multivariable glass furnace by genetic algorithm. ICAC 2014: 14-19 - [c4]Ahmed Saad Abdelhadi, J. Barry Gomm, Dingli Yu
Nonlinear system identification and control of a pH process using Local Linear Model Networks strategy. ICAC 2014: 254-259 - 2013
- [c3]Abdelkarim M. Ertiame, Dingli Yu, Feng Yu, J. B. Gomm:
Fault detection and isolation for open-loop Chylla-Haase polymerization reactor. ICAC 2013: 1-6 - 2011
- [c2]Omar Ragb, Karl O. Jones
Adaptive feed-forward and feedback control using neural networks for oxygen ratio in fuel cell stacks. CompSysTech 2011: 323-328 - [c1]Adnan Hamad, Karl O. Jones
Residual generation for fault detection of internal combustion engine. CompSysTech 2011: 329-334
2000 – 2009
- 2008
- [j11]Mahavir S. Sangha, Dingli Yu
Robustness assessment and adaptive FDI for car engine. Int. J. Autom. Comput. 5(2): 109-118 (2008) - [j10]Mahavir S. Sangha, J. Barry Gomm, Dingli Yu
Neural network fault classification of transient data in an automotive engine air path. Int. J. Model. Identif. Control. 3(2): 148-155 (2008) - 2006
- [j9]S. W. Wang, D. L. Yu
Adaptive neural network model based predictive control for air-fuel ratio of SI engines. Eng. Appl. Artif. Intell. 19(2): 189-200 (2006) - [j8]Ding-Li Yu
Neural model adaptation and predictive control of a chemical process rig. IEEE Trans. Control. Syst. Technol. 14(5): 828-840 (2006) - 2002
- [j7]D. L. Yu
Enhanced Neural Network Modelling for a Real Multi-variable Chemical Process. Neural Comput. Appl. 10(4): 289-299 (2002) - 2000
- [j6]J. B. Gomm, D. L. Yu
Order and delay selection for neural network modelling by identification of linearized models. Int. J. Syst. Sci. 31(10): 1273-1283 (2000) - [j5]J. Barry Gomm, D. L. Yu
Selecting radial basis function network centers with recursive orthogonal least squares training. IEEE Trans. Neural Networks Learn. Syst. 11(2): 306-314 (2000)
1990 – 1999
- 1997
- [j4]P. Dacosta, C. Kordich, D. Williams, J. B. Gomm:
Estimation of inaccessible fermentation states with variable inoculum sizes. Artif. Intell. Eng. 11(4): 383-392 (1997) - [j3]D. L. Yu
A Recursive Orthogonal Least Squares Algorithm for Training RBF Networks. Neural Process. Lett. 5(3): 167-176 (1997) - 1996
- [j2]George Page, Barry Gomm:
Preface. Fuzzy Sets Syst. 79(1): 1-2 (1996) - [j1]J. B. Gomm, D. Williams, J. T. Evans, S. K. Doherty, Paulo J. G. Lisboa:
Enhancing the non-linear modelling capabilities of MLP neural networks using spread encoding. Fuzzy Sets Syst. 79(1): 113-126 (1996)
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