Prof Dingli Yu

Selected Publications

  • Tok DKS, Shi Y, Tian Y, Yu D-L. 2017. Factorized f-step radial basis function model for model predictive control. NEUROCOMPUTING, vol. 239, 102-112. link> doi>
  • Deng LF, Shi YW, Zhu LX, Yu DL. 2017. Failure detection of closed-loop systems and application to SI engines. Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition), vol. 47(2), 577-582. doi>
  • Rajarathinam K, Gomm JB, Yu D, Abdelhadi AS. 2017. An improved search space resizing method for model identification by standard genetic algorithm. Systems Science & Control Engineering, vol. 5(1), 117-128. TSSC_A_1289130_2017_final.pdf doi>
  • Shi Y, Yu D-L, Tian Y, Shi Y. 2017. Modified Volterra model-based non-linear model predictive control of IC engines with real-time simulations. TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, vol. 39(2), 208-223. link> doi>
  • Zhai Y-J, Yu D-L, Qian K-J, Lee S, Theera-Umpon N. 2017. A Soft Sensor-Based Fault-Tolerant Control on the Air Fuel Ratio of Spark-Ignition Engines. ENERGIES, vol. 10(1), . M:\My Documents\My Work\Academic\Published Papers\IJISC-2007-YujiaZhai.pdf link> doi>

Other Publications

  • Zhu Q, Yu D, Zhao D. 2017. An enhanced linear Kalman filter (EnLKF) algorithm for parameter estimation of nonlinear rational models. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, vol. 48(3), 451-461. M:\My Documents\My Work\Academic\Published Papers\Zhu-Quan-2016-submitted.pdf link> doi>
  • Deng LF, Shi Y, Zhu LX, Yu DL, Zhu R. 2017. Based on the multi variable system design and parameter tuning method of PID ntroller. International Journal of Control and Automation, vol. 10(3), 1-14. doi>
  • Deng LF, Shi Y, Zhu LX, Yu DL, Zhu R. 2017. Research and application of failure detection method based on closed-loop systems. International Journal of Control and Automation, vol. 10(2), 1-12. doi>
  • Gu L, Tok DKS, Yu DL. 2016. Development of adaptive p-step RBF network model with recursive orthogonal least squares training. Neural Computing and Applications, 1-10. doi>
  • Rajarathinam K, Gomm JB, Yu DL, Abdelhadi AS. 2016. PID controller tuning for a multivariable glass furnace process by genetic algorithm. International Journal of Automation and Computing, vol. 13(1), 64-72. IJAC Journal.pdf doi>
  • Rajarathinam K, Gomm JB, Yu D, Abdelhadi AS. 2016. Model Parameters Identification for Excess Oxygen by Standard Genetic Algorithm. 22nd International Conference on Automation & Computing (ICAC). Univ Essex, Colchester, ENGLAND. In Z. Xu & J. Wang (Eds.). 2016 22ND INTERNATIONAL CONFERENCE ON AUTOMATION AND COMPUTING (ICAC) (pp. 198-203). IEEE. link> doi>
  • Rajarathinam K, Gomm JB, Yu D, Abdelhadi AS. 2015. An Improved Search Space Resizing Method for Model Identification by Standard Genetic Algorithm. 21st International Conference on Automation and Computing (ICAC). Univ Strathclyde Glasgow, Glasgow, ENGLAND. 2015 21ST INTERNATIONAL CONFERENCE ON AUTOMATION AND COMPUTING (ICAC) (pp. 383-388). IEEE. ICAC 2015 Research Paper2.pdf link> doi>
  • Shi Y, Yu D-L, Tian Y, Shi Y. 2015. Air-fuel ratio prediction and NMPC for SI engines with modified Volterra model and RBF network. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, vol. 45, 313-324. EAAI-2015-YRShi.pdf link> doi>
  • Li S, Guo P, Jiang W, Ding H, Yu D. 2015. Research on Response Characteristics and Parameters Optimization of High-speed Solenoid Valve. 34th Chinese Control Conference (CCC). Hangzhou, PEOPLES R CHINA. In Q. Zhao & S. Liu (Eds.). 2015 34TH CHINESE CONTROL CONFERENCE (CCC) (pp. 2327-2332). IEEE. link> doi>
  • Tok DKS, Yu D-L, Mathews C, Zhao D-Y, Zhu Q-M. 2015. Adaptive structure radial basis function network model for processes with operating region migration. NEUROCOMPUTING, vol. 155, 186-193. link> doi>
  • Kamal MM, Yu DW, Yu DL. 2014. Fault detection and isolation for PEM fuel cell stack with independent RBF model. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, vol. 28, 52-63. link> doi>
  • Abdelhadi A, Gomm JB, Yu D, Rajarathinam K. 2014. Comparison of RBF and Local Linear Model Networks for Nonlinear Identification of a pH Process. United-Kingdom-Automatic-Control-Council (UKACC) 10th International Conference on Control (CONTROL). Loughborough, UNITED KINGDOM. 2014 UKACC INTERNATIONAL CONFERENCE ON CONTROL (CONTROL) (pp. 361-366). IEEE. link> doi>
  • Rajarathinam K, Gomm JB, Yu D, Abdelhadi AS. 2014. Decentralised PID Control Tuning for a Multivariable Glass Furnace by Genetic Algorithm. 20th International Conference on Automation and Computing (ICAC). Cranfield Univ, Cranfield, ENGLAND. In X. Luo, Y. Cao & Z. Tong (Eds.). PROCEEDINGS OF THE 2014 20TH INTERNATIONAL CONFERENCE ON AUTOMATION AND COMPUTING (ICAC'14) (pp. 14-19). IEEE. link> doi>
  • Abdelhadi A, Gomm JB, Yu D, Rajarathinam K. 2014. Nonlinear System Identification and Control of a pH process using Local Linear Model Networks Strategy. 20th International Conference on Automation and Computing (ICAC). Cranfield Univ, Cranfield, ENGLAND. In X. Luo, Y. Cao & Z. Tong (Eds.). PROCEEDINGS OF THE 2014 20TH INTERNATIONAL CONFERENCE ON AUTOMATION AND COMPUTING (ICAC'14) (pp. 254-259). IEEE. link> doi>
  • Liu Y and Yu D-L. 2014. Robust fault detection for wind turbine systems. 20th International Conference on Automation and Computing (ICAC). Cranfield Univ, Cranfield, ENGLAND. In X. Luo, Y. Cao & Z. Tong (Eds.). PROCEEDINGS OF THE 2014 20TH INTERNATIONAL CONFERENCE ON AUTOMATION AND COMPUTING (ICAC'14) (pp. 38-42). IEEE. link> doi>
  • Ragb O, Zhao DY, Yu DL, Zhu QM. 2013. Comparison study of different non-linear feed-forward controllers for oxygen starvation control of PEM fuel cell stacks. International Journal of Modelling, Identification and Control, vol. 19(4), 352-360. doi>
  • Mahanijah MK, Yu DW, Yu DL. 2013. Fault detection and isolation based on feedforward-feedback control for oxygen excess of fuel cell stack. ICAC 2013 - Proceedings of the 19th International Conference on Automation and Computing: Future Energy and Automation, 156-160.
  • Hamad A, Zhao DY, Yu DL, Zhu QM. 2013. On-board monitoring of air path for automotive IC engines. International Journal of Modelling, Identification and Control, vol. 20(1), 1-15. doi>
  • Bian X, Yan Z, Chen T, Yu DL, Zhao Y. 2012. Mission management and control of BSA-AUV for ocean survey. OCEAN ENGINEERING, vol. 55, 161-174. link> doi>
  • Yu DL, Hamad A, Gomm JB, Sangha MS. 2014. Dynamic fault detection and isolation for automotive engine air path by independent neural network model. INTERNATIONAL JOURNAL OF ENGINE RESEARCH, vol. 15(1), 87-100. link> doi>
  • Zhai Y-J, Yu D-W, Guo H-Y, Yu DL. 2010. Robust air/fuel ratio control with adaptive DRNN model and AD tuning. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, vol. 23(2), 283-289. link> doi>
  • Zhai Y-J and Yu D-L. 2009. Neural network model-based automotive engine air/fuel ratio control and robustness evaluation. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, vol. 22(2), 171-180. link> doi>
  • Zhai YJ and Yu DL. 2008. Radial-basis-function-based feedforward-feedback control for air-fuel ratio of spark ignition engines. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, vol. 222(D3), 415-428. link> doi>
  • Wang S and Yu DL. 2008. Adaptive RBF network for parameter estimation and stable air-fuel ratio control. NEURAL NETWORKS, vol. 21(1), 102-112. link> doi>
  • Wang SW and Yu DL. 2008. Neural network-based integral sliding mode control for nonlinear uncertain systems. Lecture Notes in Electrical Engineering, vol. 5 LNEE, 245-257. doi>
  • Yu DL, Chang TK, Yu DW. 2007. A stable self-learning PID control for multivariable time varying systems. CONTROL ENGINEERING PRACTICE, vol. 15(12), 1577-1587. link> doi>
  • Wang S and Yu DL. 2007. A new development of internal combustion engine air-fuel ratio control with second-order sliding mode. JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME, vol. 129(6), 757-766. link> doi>
  • Yu DW and Yu DL. 2007. Multi-rate model predictive control of a chemical reactor based on three neural models. BIOCHEMICAL ENGINEERING JOURNAL, vol. 37(1), 86-97. link> doi>
  • Sangha MS, Yu DL, Gomm JB. 2007. Adaptive FDI for automotive engine air path and robustness assessment under closed-loop control. INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY, vol. 8(5), 637-650. link>
  • Zhai Y-J and Yu D-L. 2007. A neural network model based MPC of engine AFR with single-dimensional optimization. 4th International Symposium on Neural Networks (ISNN 2007). Nanjing, PEOPLES R CHINA. In D. Liu, S. Fei, ZG. Hou, HG. Zhang & CY. Sun (Eds.). ADVANCES IN NEURAL NETWORKS - ISNN 2007, PT 1, PROCEEDINGS (vol. 4491, pp. 339-+). SPRINGER-VERLAG BERLIN. link>
  • Wang S, Yu DL, IAENG. 2007. A new fuel injection control solution via simple and adaptive sliding mode. IMECS 2007: INTERNATIONAL MULTICONFERENCE OF ENGINEERS AND COMPUTER SCIENTISTS, VOLS I AND II (pp. 1528-1535). link>
  • Yu DL and Yu DW. 2007. A new structure adaptation algorithm for RBF networks and its application. NEURAL COMPUTING & APPLICATIONS, vol. 16(1), 91-100. link> doi>
  • Wang S and Yu DL. 2007. An application of second-order sliding mode control for IC engine fuel injection. Canadian Conference on Electrical and Computer Engineering, 1035-1038. doi>
  • Yu DL, Chang TK, Yu DW. 2007. An on-line learning algorithm of parallel mode for MLPN models. Advances in Neural Networks - ISNN 2007, Pt 2, Proceedings (vol. 4492, pp. 432-437). link>
  • Wang S and Yu D-L. 2007. Neural network in stable adaptive control law for automotive engines. 4th International Symposium on Neural Networks (ISNN 2007). Nanjing, PEOPLES R CHINA. In D. Liu, S. Fei, ZG. Hou, HG. Zhang & CY. Sun (Eds.). ADVANCES IN NEURAL NETWORKS - ISNN 2007, PT 1, PROCEEDINGS (vol. 4491, pp. 122-+). SPRINGER-VERLAG BERLIN. link>
  • Wang S and Yu DL. 2007. Neural network parameter adaptation for a fuel injection control system. Canadian Conference on Electrical and Computer Engineering, 558-561. doi>
  • Wang S, Yu DL, IAENG. 2007. Robust integral sliding mode control against matched and unmatched system uncertainty. IMECS 2007: INTERNATIONAL MULTICONFERENCE OF ENGINEERS AND COMPUTER SCIENTISTS, VOLS I AND II (pp. 1483-1488). link>
  • Sangha MS, Yu DL, Gomm JB. 2006. On-board monitoring and diagnosis for spark ignition engine air path via adaptive neural networks. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, vol. 220(D11), 1641-1655. link> doi>
  • Yu D-L, Yu D-W, Gomm JB. 2006. Neural model adaptation and predictive control of a chemical process rig. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, vol. 14(5), 828-840. link> doi>
  • Wang SW, Yu DL, Gomm JB, Page GF, Douglas SS. 2006. Adaptive neural network model based predictive control for air-fuel ratio of SI engines. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, vol. 19(2), 189-200. link> doi>
  • Wang SW, Yu DL, Gomm IB, Page GF, Douglas SS. 2006. Adaptive neural network model based predictive control of an internal combustion engine with a new optimization algorithm. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, vol. 220(D2), 195-208. link> doi>
  • Yu D-W and Yu D-L. 2006. Adaptive pseudo linear RBF model for process control. 3rd International Symposium on Neural Networks (ISNN 2006). Chengdu, PEOPLES R CHINA. In J. Wang, Z. Yi, JM. Zurada, BL. Lu & H. Yin (Eds.). ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 2, PROCEEDINGS (vol. 3972, pp. 1013-1018). SPRINGER-VERLAG BERLIN. link> doi>
  • Wang S, Yu DL, IEEE. 2006. An application of second-order sliding mode control for ic engine fuel injection. 2006 Canadian Conference on Electrical and Computer Engineering, Vols 1-5 (pp. 961-964). link>
  • Yu D-L and Chang T-K. 2006. Fault diagnosis with enhanced neural network modelling. 3rd International Symposium on Neural Networks (ISNN 2006). Chengdu, PEOPLES R CHINA. In J. Wang, Z. Yi, JM. Zurada, BL. Lu & H. Yin (Eds.). ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 3, PROCEEDINGS (vol. 3973, pp. 358-363). SPRINGER-VERLAG BERLIN. link>
  • Wang S, Yu DL, IEEE. 2006. Neural network parameter adaptation for a fuel injection control. 2006 Canadian Conference on Electrical and Computer Engineering, Vols 1-5 (pp. 981-984). link>
  • Yu DW and Yu DL. 2005. Modeling a multivariable reactor and on-line model predictive control. ISA TRANSACTIONS, vol. 44(4), 539-559. link> doi>
  • Yu DL and Chang TK. 2005. Adaptation of diagonal recurrent neural network model. NEURAL COMPUTING & APPLICATIONS, vol. 14(3), 189-197. link> doi>
  • Yu DL, Chang TK, Yu DW. 2005. Adaptive neural model-based fault tolerant control for multi-variable processes. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, vol. 18(4), 393-411. link> doi>
  • Yu DL, Chang TK, Yu DW. 2005. Fault tolerant control of multivariable processes using auto-tuning PID controller. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, vol. 35(1), 32-43. link> doi>
  • Beham M and Yu DL. 2005. On-line control for optimal ignition timing using the pseudolinear radial basis function and the local linear model tree. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, vol. 219(D2), 227-240. link> doi>
  • Yu DL, Yu DW, Gomm JB, Page GF. 2005. A new development of adaptive model predictive control. IFAC Proceedings Volumes (IFAC-PapersOnline), vol. 16, 348-353. doi>
  • Wang SW, Yu DL, Gomm JB, Beham M, Page GF, Douglas SS. 2005. Adaptive modelling and predictive control of an IC engine. IFAC Proceedings Volumes (IFAC-PapersOnline), vol. 16, 242-247. doi>
  • Yu DL and Beham M. 2005. Comparative study on engine torque modelling using different neural networks. 2nd International Symposium on Neural Networks. Chongqing, PEOPLES R CHINA. In J. Wang, X. Liao & Z. Yi (Eds.). ADVANCES IN NEURAL NETWORKS - ISNN 2005, PT 3, PROCEEDINGS (vol. 3498, pp. 865-870). SPRINGER-VERLAG BERLIN. link>
  • Yu DL and Yu DW. 2005. Detecting sensor faults for a chemical reactor rig via adaptive neural network model. 2nd International Symposium on Neural Networks. Chongqing, PEOPLES R CHINA. In J. Wang, X. Liao & Z. Yi (Eds.). ADVANCES IN NEURAL NETWORKS - ISNN 2005, PT 3, PROCEEDINGS (vol. 3498, pp. 544-549). SPRINGER-VERLAG BERLIN. link>
  • Sangha MS, Gomm JB, Yu DL, Page GF. 2005. Fault detection and identification of automotive engines using neural networks. IFAC Proceedings Volumes (IFAC-PapersOnline), vol. 16, 272-277. doi>
  • Yu DL, Chang TH, Wang J. 2005. Fault tolerant control of nonlinear processes with adaptive diagonal recurrent neural network model. 2nd International Symposium on Neural Networks. Chongqing, PEOPLES R CHINA. In J. Wang, X. Liao & Z. Yi (Eds.). ADVANCES IN NEURAL NETWORKS - ISNN 2005, PT 3, PROCEEDINGS (vol. 3498, pp. 86-91). SPRINGER-VERLAG BERLIN. link>
  • Yu DL. 2004. A localized forgetting method for Gaussian RBFN model adaptation. NEURAL PROCESSING LETTERS, vol. 20(2), 125-135. link> doi>
  • Beham M and Yu DL. 2004. Modelling a variable valve timing spark ignition engine using different neural networks. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, vol. 218(10), 1159-1171.
  • Beham M and Yu DL. 2004. Modelling a variable valve timing spark ignition engine using different neural networks. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, vol. 218(D10), 1159-1171. link> doi>
  • Wang J, Sii HS, Yang JB, Pillay A, Yu D, Liu J, Maistralis E, A Saajedi. 2004. Use of advances in technology for maritime risk assessment. Risk Anal, vol. 24(4), 1041-1063. link> doi>
  • Beham M, Etzel M, Yu DL. 2004. Development of a new automatic calibration method for control of variable valve timing. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, vol. 218(D7), 707-718. link> doi>
  • Yu DL, Yu DW, Gomm JB, Page GF. 2004. Adaptive RBF model for model-based control. Proceedings of the World Congress on Intelligent Control and Automation (WCICA), vol. 1, 78-82.
  • Chang TK, Yu DL, Yu DW. 2004. Neural network model adaptation and its application to process control. ADVANCED ENGINEERING INFORMATICS, vol. 18(1), 1-8. link> doi>
  • Yu DW and Yu DL. 2003. Neural network control of multivariable processes with a fast optimisation algorithm. NEURAL COMPUTING & APPLICATIONS, vol. 12(3-4), 185-189. link> doi>
  • Yu DL and Gomm JB. 2003. Implementation of neural network predictive control to a multivariable chemical reactor. 14th IFAC World Congress. BEIJING, PEOPLES R CHINA. CONTROL ENGINEERING PRACTICE (vol. 11, pp. 1315-1323). PERGAMON-ELSEVIER SCIENCE LTD. link> doi>
  • Yu DW and Yu DL. 2003. A comparison study on a chemical reactor modelling with a physical model and PLRBF networks. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, vol. 16(7-8), 629-645. link> doi>
  • Yu DL and Yu DW. 2003. A linear parameter-varying radial basis function model and predictive control of a chemical reactor. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, vol. 34(14-15), 747-761. link> doi>
  • Chang TK, Yu DL, Williams D. 2002. A parallel MLPN model with EKF-based on-line learning algorithm. IFAC Conference on Control Applications in Marine Systems. UNIV STRATHCLYDE, GLASGOW, SCOTLAND. In R. Katebi (Ed.). CONTROL APPLICATIONS IN MARINE SYSTEMS 2001 (CAMS 2001) (pp. 499-504). PERGAMON-ELSEVIER SCIENCE LTD. link>
  • Yu DL and Gomm JB. 2002. Enhanced neural network modelling for a real multivariable chemical process. NEURAL COMPUTING & APPLICATIONS, vol. 10(4), 289-299. link> doi>
  • Chang TK, Yu DL, Williams D. 2002. Enhanced neural network modelling for process fault diagnosis. IFAC Conference on Control Applications in Marine Systems. UNIV STRATHCLYDE, GLASGOW, SCOTLAND. In R. Katebi (Ed.). CONTROL APPLICATIONS IN MARINE SYSTEMS 2001 (CAMS 2001) (pp. 215-220). PERGAMON-ELSEVIER SCIENCE LTD. link>
  • Chang TK and Yu DL. 2002. Fault-tolerant control based on adaptive neural network. IFAC Conference on Control Applications in Marine Systems. UNIV STRATHCLYDE, GLASGOW, SCOTLAND. In R. Katebi (Ed.). CONTROL APPLICATIONS IN MARINE SYSTEMS 2001 (CAMS 2001) (pp. 77-82). PERGAMON-ELSEVIER SCIENCE LTD. link>
  • Yu DL, Yu DW, Gomm JB, Williams D. 2002. Model predictive control of a chemical process based on an adaptive neural network. IFAC Proceedings Volumes (IFAC-PapersOnline) (vol. 15, pp. 295-300). doi>
  • Yu DL and Gomm JB. 2002. RBFN model adaptation based on orthogonal decomposition. IFAC Workshop on Adaptation and Learning in Control and Signal Processing. CERNOBBIO COMO, ITALY. In S. Bittanti (Ed.). ADAPTATION AND LEARNING IN CONTROL AND SIGNAL PROCESSING 2001 (pp. 101-106). PERGAMON-ELSEVIER SCIENCE LTD. link>
  • Yu DL and Shields DN. 2001. Extension of the parity-space method to fault diagnosis of bilinear systems. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, vol. 32(8), 953-962. link> doi>
  • Gomm JB and Yu DL. 2000. Order and delay selection for neural network modelling by identification of linearized models. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, vol. 31(10), 1273-1283. link> doi>
  • Yu DL. 2000. Diagnosing simulated faults for an industrial furnace based on bilinear model. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, vol. 8(3), 435-442. link> doi>
  • Yu DL, Williams D, Gomm JB. 2000. On-line implementation of a neural network model predictive controller. IEE Colloquium (Digest), 39-42.
  • Yu DL, Gomm JB, Williams D. 2000. Neural model input selection for a MIMO chemical process. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, vol. 13(1), 15-23. link> doi>
  • Gomm JB and Yu DL. 2000. Selecting radial basis function network centers with recursive orthogonal least squares training. IEEE TRANSACTIONS ON NEURAL NETWORKS, vol. 11(2), 306-314. link> doi>
  • Yu DL, Williams D, Gomm JB. 1999. On-line implementation of a model predictive controller on a multivariable chemical process. IEE Colloquium (Digest), 5-9.
  • Yu DL, Gomm JB, Williams D. 1999. Sensor fault diagnosis in a chemical process via RBF neural networks. CONTROL ENGINEERING PRACTICE, vol. 7(1), 49-55. link> doi>
  • Yu DL and Shields DN. 1998. An extended parity space method and a case study on an industrial furnace. 3rd IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes 1997 (SAFEPROCESS 97). KINGSTON HULL, ENGLAND. In RJ. Patton & J. Chen (Eds.). (SAFEPROCESS'97): FAULT DETECTION, SUPERVISION AND SAFETY FOR TECHNICAL PROCESSES 1997, VOLS 1-3 (pp. 771-776). PERGAMON PRESS LTD. link>
  • Yu DL. 1998. Application of parameter estimation method to fault diagnosis of a hydraulic system. 11th IFAC Symposium on System Identification (SYSID 97). KITAKYUSHU, JAPAN. In Y. Sawaragi & S. Sagara (Eds.). (SYSID'97): SYSTEM IDENTIFICATION, VOLS 1-3 (pp. 609-614). PERGAMON PRESS LTD. link>
  • Yu DL, Gomm JB, Williams D. 1998. Diagnosing sensor faults in a chemical process via rbf networks. 3rd IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes 1997 (SAFEPROCESS 97). KINGSTON HULL, ENGLAND. In RJ. Patton & J. Chen (Eds.). (SAFEPROCESS'97): FAULT DETECTION, SUPERVISION AND SAFETY FOR TECHNICAL PROCESSES 1997, VOLS 1-3 (pp. 893-898). PERGAMON PRESS LTD. link>
  • Yu DL, Gomm JB, Williams D. 1998. Model predictive control of a chemical process using neural network. UKACC International Conference on Control 98. UNIV WALES UNIV COLL SWANSEA, SWANSEA, WALES. UKACC INTERNATIONAL CONFERENCE ON CONTROL '98, VOLS I&II (pp. 798-803). INST ELECTRICAL ENGINEERS INSPEC INC. link>
  • Yu DL, Gomm JB, Williams D. 1998. Modelling a MIMO chemical process using a RBF network with recursive OLS updating. 11th IFAC Symposium on System Identification (SYSID 97). KITAKYUSHU, JAPAN. In Y. Sawaragi & S. Sagara (Eds.). (SYSID'97): SYSTEM IDENTIFICATION, VOLS 1-3 (pp. 549-554). PERGAMON PRESS LTD. link>
  • Yu DL, Gomm JB, Williams D. 1998. Selection of neural model order and time-delay for MIMO non-linear systems and a case study on a CSTR process. 11th IFAC Symposium on System Identification (SYSID 97). KITAKYUSHU, JAPAN. In Y. Sawaragi & S. Sagara (Eds.). (SYSID'97): SYSTEM IDENTIFICATION, VOLS 1-3 (pp. 227-232). PERGAMON PRESS LTD. link>
  • Yu DL and Shields DN. 1997. A bilinear fault detection filter. INTERNATIONAL JOURNAL OF CONTROL, vol. 68(3), 417-430. link> doi>
  • Yu D. 1997. Fault diagnosis for a hydraulic drive system using a parameter-estimation method. CONTROL ENGINEERING PRACTICE, vol. 5(9), 1283-1291. link> doi>
  • Yu DL, Gomm JB, Williams D. 1997. A recursive orthogonal least squares algorithm for training RBF networks. NEURAL PROCESSING LETTERS, vol. 5(3), 167-176. link> doi>
  • Yu DL, Shields DN, Disdell K. 1996. A simulation study on fault diagnosis of a high-temperature furnace using a bilinear observer method. CONTROL ENGINEERING PRACTICE, vol. 4(12), 1681-1691. link> doi>
  • Yu D and Shields DN. 1996. A bilinear fault detection observer. 2nd IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS 94). ESPOO, FINLAND. AUTOMATICA (vol. 32, pp. 1597-1602). PERGAMON-ELSEVIER SCIENCE LTD. link> doi>
  • Yu DL, Shields DN, Daley S. 1996. A bilinear fault detection observer and its application to a hydraulic drive system. INTERNATIONAL JOURNAL OF CONTROL, vol. 64(6), 1023-1047. link> doi>
  • Gomm JB, Yu DL, Williams D. 1996. New model structure selection method for non-linear systems in neural modelling. IEE Conference Publication, 752-757.
  • YU DL, WILLIAMS D, SHIELD DN, GOMM JB. 1995. A parity space method of fault detection for bilinear systems. 1995 American Control Conference. SEATTLE, WA. PROCEEDINGS OF THE 1995 AMERICAN CONTROL CONFERENCE, VOLS 1-6 (pp. 1132-1133). AMER AUTOMATIC CONTROL COUNCIL. link>
  • Yu DL, Shields DN, Daley S. 1995. Application of radial basis function networks to fault diagnosis for a hydraulic system. International Conference on Artificial Neural Nets and Genetic Algorithms. ALES, FRANCE. In DW. Pearson, NC. Steele & RF. Albrecht (Eds.). ARTIFICIAL NEURAL NETS AND GENETIC ALGORITHMS (pp. 100-103). SPRINGER-VERLAG. link>
  • YU DL, GOMM JB, SHIELDS DN, WILLIAMS D, DISDELL K. 1995. Fault diagnosis for a gas-fired furnace using bilinear observer method. 1995 American Control Conference. SEATTLE, WA. PROCEEDINGS OF THE 1995 AMERICAN CONTROL CONFERENCE, VOLS 1-6 (pp. 1127-1131). AMER AUTOMATIC CONTROL COUNCIL. link>
  • Yu DL and Shields DN. 1995. Optimally robust fault diagnosis using genetic algorithms. International Conference on Artificial Neural Nets and Genetic Algorithms. ALES, FRANCE. In DW. Pearson, NC. Steele & RF. Albrecht (Eds.). ARTIFICIAL NEURAL NETS AND GENETIC ALGORITHMS (pp. 104-107). SPRINGER-VERLAG. link>
  • YU DL, SHIELDS DN, MAHTANI JL. 1994. A NONLINEAR FAULT-DETECTION METHOD FOR A HYDRAULIC SYSTEM. International Conference on Control 94. UNIV WARWICK, COVENTRY, ENGLAND. INTERNATIONAL CONFERENCE ON CONTROL 94, VOLS 1 AND 2 (pp. 1318-1322). INST ELECTRICAL ENGINEERS. link>
  • YU DL, SHIELDS DN, MAHTANI JL. 1994. FAULT-DETECTION FOR BILINEAR-SYSTEMS WITH APPLICATION TO A HYDRAULIC SYSTEM. 3rd IEEE Conference on Control Applications. IMOV STRATHCLYDE, GLASGOW, SCOTLAND. PROCEEDINGS OF THE THIRD IEEE CONFERENCE ON CONTROL APPLICATIONS, VOLS 1-3 (pp. 1379-1384). I E E E. link> doi>
  • Rajarathinam K. Advanced PID Control Optimisation and System Identification for Multivariable Glass Furnace Processes by Genetic Algorithms. 2016kumaranphd.pdf
  • Chen X, Sufian M, Yu D. Investigating the Capability of Precision in Robotic Grinding. Xplore, the 23rd International Conference on Automation & Computing. D:\LJMU-Works\R\Publication\ICAC\ICAC'17\Mo\p_66 published.pdf
  • Ertiame AM, Yu D, Yu F, Gomm JB. 2015. Robust fault diagnosis for an exothermic semi-batch polymerization reactor under open-loop. Systems Science and Control Engineering, vol. 3(1), 14-23. doi>


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