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Papers by Ming Tham

Automatica, 1996

Differential geometry is used to investigate the structure of neural-network-based control system... more Differential geometry is used to investigate the structure of neural-network-based control systems. The key aspect is relative order—an invariant property of dynamic systems. Finite relative order allows the specification of a minimal architecture for a recurrent network. Any system with finite relative order has a left inverse. It is shown that a recurrent network with finite relative order has a local inverse that is also a recurrent network with the same weights. The results have implications for the use of recurrent networks in the inverse-model-based control of nonlinear systems.

Mathematics and Computers in Simulation, 2000

This paper illustrates how internal model control of nonlinear processes can be achieved by recur... more This paper illustrates how internal model control of nonlinear processes can be achieved by recurrent neural networks, e.g. fully connected Hopfield networks. It is shown that using results developed by Kambhampati et al. (1995), that once a recurrent network model of a nonlinear system has been produced, a controller can be produced which consists of the network comprising the inverse of the model and a filter. Thus, the network providing control for the nonlinear system does not require any training after it has been trained to model the nonlinear system. Stability and other issues of importance for nonlinear control systems are also discussed.

Digital Computer Applications to Process Control, 1986

2006 SICE-ICASE International Joint Conference, 2006

Maximum sensitivity, M5, is a closed-loop design specification that satisfies many of the require... more Maximum sensitivity, M5, is a closed-loop design specification that satisfies many of the requirements of a useful and practical PID controller tuning method. A variety of PID tuning methods using this specification have been developed with the majority being developed primarily for auto-tuning purposes. This contribution examines the general applicability of a number of the tuning methods by comparing their performance on some benchmark process plant models.

Lecture Notes in Control and Information Sciences, 1991

ABSTRACT Two different approaches that can provide frequent and accurate estimates of process out... more ABSTRACT Two different approaches that can provide frequent and accurate estimates of process outputs which are subject to large measurement delays are outlined. The first is based upon linear adaptive techniques whilst the other makes use of a fixed parameter neural network model. The results of applications to industrial data are used to discuss and contrast the performance capabilities of the two techniques.

ABSTRACT This paper provides a contribution to Qualitative Reasoning for distillation process sup... more ABSTRACT This paper provides a contribution to Qualitative Reasoning for distillation process supervision. Initial results using a Qualitative Physics to model physical systems have been encouraging, but scaling the approach to realistic problems does not appear as straightforward as initially expected. An approach based on Transfer Function theory is proposed with an application study to a computer simulation of a distillation process. Using a numerical model of the process as a reference, the relevancy of the information provided by the Qualitative Transfer Function-based model is demonstrated. A second model is proposed, which takes into account the mass balance inside the column using approximate knowledge on the relationships between the physical variables involved. The qualitative aspects of the approach allow to capture non-numerical information which is sometimes very useful for supervision purposes.

Process Control is acknowledged to be the technology that has the greatest potential for improvin... more Process Control is acknowledged to be the technology that has the greatest potential for improving competitiveness in the process industries. Although Chemical/Process Engineers are the natural personnel to carry out Process Control functions, as undergraduates, they often view Process Control to be a subject full of abstract concepts with high mathematical content and hence difficult; and that Process Control is non-mainstream Chemical Engineering. Many are therefore put off by Process Control at an early stage. Laboratories are traditionally used to mitigate this situation, and more recently, computer delivered interactive content have also been reported to be an useful tool in Process Control education. However, both have, up to now, been used as separate teaching tools. This paper proposes a framework whereby the two approaches can be integrated into a Process Engineering virtual teaching environment. Technical and implementation issues are also discussed.

Automatica, 1996

Differential geometry is used to investigate the structure of neural-network-based control system... more Differential geometry is used to investigate the structure of neural-network-based control systems. The key aspect is relative order—an invariant property of dynamic systems. Finite relative order allows the specification of a minimal architecture for a recurrent network. Any system with finite relative order has a left inverse. It is shown that a recurrent network with finite relative order has a local inverse that is also a recurrent network with the same weights. The results have implications for the use of recurrent networks in the inverse-model-based control of nonlinear systems.

Mathematics and Computers in Simulation, 2000

This paper illustrates how internal model control of nonlinear processes can be achieved by recur... more This paper illustrates how internal model control of nonlinear processes can be achieved by recurrent neural networks, e.g. fully connected Hopfield networks. It is shown that using results developed by Kambhampati et al. (1995), that once a recurrent network model of a nonlinear system has been produced, a controller can be produced which consists of the network comprising the inverse of the model and a filter. Thus, the network providing control for the nonlinear system does not require any training after it has been trained to model the nonlinear system. Stability and other issues of importance for nonlinear control systems are also discussed.

Digital Computer Applications to Process Control, 1986

2006 SICE-ICASE International Joint Conference, 2006

Maximum sensitivity, M5, is a closed-loop design specification that satisfies many of the require... more Maximum sensitivity, M5, is a closed-loop design specification that satisfies many of the requirements of a useful and practical PID controller tuning method. A variety of PID tuning methods using this specification have been developed with the majority being developed primarily for auto-tuning purposes. This contribution examines the general applicability of a number of the tuning methods by comparing their performance on some benchmark process plant models.

Lecture Notes in Control and Information Sciences, 1991

ABSTRACT Two different approaches that can provide frequent and accurate estimates of process out... more ABSTRACT Two different approaches that can provide frequent and accurate estimates of process outputs which are subject to large measurement delays are outlined. The first is based upon linear adaptive techniques whilst the other makes use of a fixed parameter neural network model. The results of applications to industrial data are used to discuss and contrast the performance capabilities of the two techniques.

ABSTRACT This paper provides a contribution to Qualitative Reasoning for distillation process sup... more ABSTRACT This paper provides a contribution to Qualitative Reasoning for distillation process supervision. Initial results using a Qualitative Physics to model physical systems have been encouraging, but scaling the approach to realistic problems does not appear as straightforward as initially expected. An approach based on Transfer Function theory is proposed with an application study to a computer simulation of a distillation process. Using a numerical model of the process as a reference, the relevancy of the information provided by the Qualitative Transfer Function-based model is demonstrated. A second model is proposed, which takes into account the mass balance inside the column using approximate knowledge on the relationships between the physical variables involved. The qualitative aspects of the approach allow to capture non-numerical information which is sometimes very useful for supervision purposes.

Process Control is acknowledged to be the technology that has the greatest potential for improvin... more Process Control is acknowledged to be the technology that has the greatest potential for improving competitiveness in the process industries. Although Chemical/Process Engineers are the natural personnel to carry out Process Control functions, as undergraduates, they often view Process Control to be a subject full of abstract concepts with high mathematical content and hence difficult; and that Process Control is non-mainstream Chemical Engineering. Many are therefore put off by Process Control at an early stage. Laboratories are traditionally used to mitigate this situation, and more recently, computer delivered interactive content have also been reported to be an useful tool in Process Control education. However, both have, up to now, been used as separate teaching tools. This paper proposes a framework whereby the two approaches can be integrated into a Process Engineering virtual teaching environment. Technical and implementation issues are also discussed.

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