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Optimization of block-floating-point realizations for digital controllers with finite-word-length considerations

Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2003年第6期4卷 30-36页

作者：吴俊胡协和陈生褚健 Department of Electronics and Computer Science Zhejiang University Southampton SO17 1BJ National Key Laboratory of Industrial Control Technology National Key Laboratory of Industrial Control Technology Institute of Advanced Process Control China Hangzhou 310027 UK University of Southampton

The closed loop stability issue of finite precision realizations was investigated for digital controllers implemented in block floating point format. The controller coefficient perturbation was analyzed resulting from using finite word length (FWL) block floating point representation scheme. A block floating point FWL closed loop stability measure was derived which considers both the dynamic range and precision. To facilitate the design of optimal finite precision controller realizations, a computationally tractable block floating point FWL closed loop stability measure was then introduced and the method of computing the value of this measure for a given controller realization was developed. The optimal controller realization is defined as the solution that maximizes the corresponding measure, and a numerical optimization approach was adopted to solve the resulting optimal realization problem. A numerical example was used to illustrate the design procedure and to compare the optimal controller realization with the initial realization.

关键词： Digital controller Finite word length Block floating point Closed loop stability Optimization

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Research on an integrated ICA-SVM based framework for fault diagnosis

Research on an integrated ICA-SVM based framework for fault ...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Ming Guo Lei Xie Shu-Qing Wang Jian-Ming Zhang National Key Laboratory of Industrial Control Technology Institute of Advanced Process Control Zhejiang University of Technology Hangzhou China

ISBN: (纸本)0780379527

A chemical process has a large number of measured variables, but it is usually driven by fewer essential variables, which may not be measured. Extracting these essential variables and monitoring them will improve the process monitoring performance. In this paper, an integrated framework for process monitoring and fault diagnosis is presented, which combines independent component analysis (ICA) for feature extraction and a support vector machine (SVM) for identification of different fault source. ICA is used to determine the projection coefficient matrix which represents the features characterizing the current operating condition. Well-trained multiple support vector machines use the projection coefficient matrix as their input to identify the faults. The method is proved to be effective by an application to monitoring of the Tennessee Eastman process.

关键词： Fault diagnosis Independent component analysis Support vector machines Principal component analysis Chemical processes process control Biomedical measurements Biomedical monitoring Feature extraction Condition monitoring

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Block Recursive MPCA and its application in batch process monitoring

Block Recursive MPCA and its application in batch process mo...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Lei Xie Ning He Shu-Qing Wang Jian-Ming Zhang National Key Laboratory of Industrial Control Technology Research Institute of Advanced Process Control Zhejiang University of Technology Hangzhou China

ISBN: (纸本)0780379527

A new approach, Block Recursive MPCA, to monitor batch process based on the process variables trajectories is proposed. It is cumbersome to overcome the traditional MPCA's need of estimating or filling in the unknown part of the process variable trajectory deviations from the current time to the end. To tackle the problem, Block Recursive MPCA method involves a sequential of PCA models and forgetting factors among them to analyze the 3-dimension history data. In addition, a method for calculating the distance between PCA models is proposed to evaluate the forgetting factor. Application in industrial fermentation batch process reveals that Block Recursive MPCA describes the process more accurately and objectively than traditional MPCA.

关键词： Monitoring Principal component analysis Chemical industry process control History Manufacturing industries Chemical analysis Multiprotocol label switching Matrix decomposition Helium

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Linear pruning techniques for neural networks-based on projection latent structure

Linear pruning techniques for neural networks-based on proje...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Lei Xie Quan-Ling Zhang Ming Guo Shu-Qing Wang National Key Laboratory of Industrial Control Technology Research Institute of Advanced Process Control Zhejiang University of Technology Hangzhou China

ISBN: (纸本)0780379527

Based on a 5-layer neural network, nonlinear principal component analysis (NLPCA) has been widely applied in many problems. However, when applying NLPCA in modeling and monitoring chemical process, it's hard to determine the number of hidden layer's nodes. This results in a tendency to use networks much larger than required. A brief review of presented linear neural network pruning techniques is given, and an improved linear pruning method based on Projection Latent Structure (PLS) is presented. The advantages of propose approaches are discussed and illustrated via modeling the famous Tennessee Eastman chemical process.

关键词： Neural networks Principal component analysis Chemical processes Monitoring Biological system modeling Laboratories industrial control Chemical technology process control Chemistry

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Neuro-fuzzy control for turning processes

Neuro-fuzzy control for turning processes

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American control Conference (ACC)

作者： Ning Wang Jun Liang Guang Yang National Key Laboratory of Industrial Control Technology And Research Institute of Advanced Process Control University of Zhejiang Hangzhou Zhejiang China

ISBN: (纸本)0780378962

The neuro-fuzzy control method for a constant cutting force metal turning process is proposed in this paper. The model of a turning process is described. After discussing the neuron controller and a basic fuzzy controller, the neuro-fuzzy control system is designed. The new model-free controller is combined with both the neuron controller and fuzzy controller. The simulation results of using the proposed controller for a cutting process show that this controller has very strong robustness and good performance.

关键词： process control Turning Neurons Automatic control control systems Fuzzy control Force control Servosystems Feeds Shape control

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Neuro-fuzzy network based on rough sets and its applications

Neuro-fuzzy network based on rough sets and its applications

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IEEE International Conference on Systems, Man and Cybernetics

作者： Jianming Zhang Shuqing Wang Lei Xie National Key Laboratory of Industrial Control Technology and Research Institute of Advanced Process Control Zhejiang University of Technology Hangzhou China

ISBN: (纸本)0780379527

A new constructive method of the neuro-fuzzy network based on rough sets is proposed. First, an initial fuzzy rule base is generated from the history input-output data pairs by rough sets approach. Then, a neuro-fuzzy network is formed according to the rule table. And the learning algorithm based on the gradient descent method is given. The major advantage of this approach is to optimize the overall structure of the neuro-fuzzy network as well as to adjust each parameter of fuzzy rules without doing the complicated clustering process. Finally, the efficiency of the new method is illustrated by means of applying to truck backer-upper control.

关键词： Fuzzy neural networks Rough sets Fuzzy systems Fuzzy control Signal processing algorithms Laboratories industrial control process control Neural networks Clustering algorithms

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Model-free PID controller with gain scheduling for turning processes

Model-free PID controller with gain scheduling for turning p...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Ning Wang Zhong Zheng Honglu Chen National Key Laboratory of Industrial Control Technology And Research Inst. of Advanced Process Control Zhejiang University of Technology Hangzhou China National Key Lab. of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (纸本)0780379527

The model-free PID control method with fuzzy neuron gain scheduling is proposed for turning processes in this paper. In order to enhance the control system stability and adaptability to the plants with nonlinearities and uncertainties, the model-free PID controller is designed to keep the cutting force to be constant by changing the controller gain on-line when a cutting tool cuts at various cutting depth or the spindle operates in different speeds. In this control system, the PID controller is used to control the turning process, the neuron is applied to tune the PID controller gain, and a fuzzy scheme is set up to change the neuron gain. With the two examples of different turning processes, the experiments of using the proposed control method are made. The simulation results show the good performance of the model-free PID controller.

关键词： Three-term control Turning control systems Neurons Force control Nonlinear control systems control nonlinearities Fuzzy control control system synthesis Stability

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Neuron double-layer control

Neuron double-layer control

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Ning Wang National Key Laboratory of Industrial Control Technology And Research Institute of Advanced Process Contro1 University of Zhejiang Hangzhou China

ISBN: (纸本)0780378652

The neuron PID double-layer control system is set up and the double-layer control method is proposed for control system with uncertainties in this paper. In this control system, a conventional PID controller is used in the insider layer control loop, and the neuron model-free controller is used in the outsider layer control loop. As a result of utilizing the double layer control structure, the PID control parameters can be selected imprecisely and the control system dynamics can be improved efficiently. The application of the proposed control method to the liquid level control of a tower of the fluid catalytic cracking unit (FCCU) is described. The excellent performance obtained in practice shows that the new control method has powerful vitality in industrial control.

关键词： Neurons control systems Three-term control Uncertainty Machine learning industrial control Level control Poles and towers control system synthesis Hebbian theory

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An intelligent controller based on two neurons

An intelligent controller based on two neurons

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Ning Wang Jian-Hua Wu National Key Laboratory of Industrial Control Technology And Research Institute of Advanced Process Control University of Zhejiang Hangzhou China College of Electrical Engineering University of Zhejiang Hangzhou China

ISBN: (纸本)0780378652

According to the neuron model and its learning strategy in [Wang Ning et al., 1991], the intelligent control method based on two neurons is presented in this paper. In this control system, the two neurons are used to structure the compound controller. One neuron acts as a feed-forward and PD controller, the other neuron acts as a PI controller. With an example of basis weight control, the simulation tests are made to demonstrate the effectiveness of the proposed controller in handing plants with uncertainties.

关键词： Neurons control systems Intelligent control Uncertainty Weight control industrial control process control Paper making machines Three-term control Electrical equipment industry

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Nonlinear neuron control of a direct drive robot

Nonlinear neuron control of a direct drive robot

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IEEE International Conference on Systems, Man and Cybernetics

作者： Ning Wang Jianhua Wu National Key Laboratory of Industrial Control Technology And Research Inst. of Advanced Process Control Zhejiang University of Technology Hangzhou China College of Electrical Engineering Zhejiang University of Technology Hangzhou China

ISBN: (纸本)0780379527

The nonlinear neuron control method is proposed for a direct drive robot in this paper. In this control system, the neuron controller and the relay controller are designed in parallel connection to form the model-free controller to control a direct drive robot with uncertainties. A fuzzy scheme is used to tune the relay controller gain on line. With an example of a direct drive robot manipulator, the experiments are made. The simulation results demonstrate that the proposed method can efficiently control the independent joint of the direct drive robot. This model-free controller has excellent performance, strong robustness and adaptability.

关键词： Neurons Nonlinear control systems control systems Sliding mode control Manipulator dynamics Service robots Pulse width modulation Uncertainty Fuzzy control Robot control

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