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Digital imaging and piezo-dispenser actuator in automatic flocculation control

Sensors and Transducers 2012年第1期136卷 83-95页

作者： Tomperi, Jani Honkanen, Markus Kallio, Pasi Leiviskä, Kauko Saarenrinne, Pentti Joensuu, Iiris Piironen, Marjatta Control Engineering Laboratory Department of Process and Environmental Engineering University of Oulu P. O Box 4300 FIN-90014 Finland Tampere University of Technology Department of Energy and Process Engineering P. O. Box 589 FIN-33101 Tampere Finland Tampere University of Technology Department of Automation Science and Engineering P. O. Box 692 FIN-33101 Tampere Finland Kemira Oyj Espoo R and D Center P. O. Box 44 FIN-02271 Espoo Finland

This study presents an image-based on-line control system for a coiled pipe flocculator. A digital imaging technique developed previously is utilized to measure the characteristic floc size and a high-pressure piezo-dispenser is introduced for accurate dosing and rapid mixing of the flocculant. The controller is a conventional PI controller. Step change experiments on feed water quality, flow rate and desired floc size have been carried out for controller tuning and testing. The paper shows that the piezo-dispenser provides better flocculation results than a conventional dosing pump, and the flocculation result can be automatically controlled even when the feed water quality rapidly changes. The proposed flocculator is a simple, inexpensive and practical system for long-term laboratory tests to investigate the functionality of flocculants on varying feed *** © 2012 IFSA.

关键词： Water treatment

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Distributed ANNs in a layered architecture for energy management and maintenance scheduling of renewable energy HPS microgrids

Distributed ANNs in a layered architecture for energy manage...

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International Conference on Advances in Power Conversion and Energy Technologies (APCET)

作者： Y Jaganmohan Reddy Y V Pavan Kumar V Sunil Kumar K Padma Raju Process Solutions-Automation & Control Solutions Honeywell Technology Solutions Lab (Pvt) Ltd Hyderabad India Engineering Test Services-Aerospace Honeywell Technology Solutions Lab (Pvt) Ltd Hyderabad India Department of Electronics and Communication Engineering Jawaharlal Nehru Technological University Kakinada (JNTUK) Kakinada India

With increasing research on the field of alternative energy resources for sustainable development, more renewable energy sources are getting penetrated to the distributed network to form “microgrid”. This leads to more complexity in the distribution network in terms of energy management and realtime control. The objective of this paper is to design a system that forecasts the short (daily), medium (seasonal) and long term (yearly) load demand and the availability of energy resources at the microgrids. For scheduling the storage and transaction of electrical energy between neighboring microgrids, an energy management system (EMS) is designed. The EMS makes use of the forecasted data and real time data all together for managing an array of interconnected microgrids. The seasonal and yearly forecaster for a geographical boundary helps in maintenance scheduling and long term infrastructure development plan respectively. Recently, Artificial Neural Network (ANN) is found as a promising tool for statistical forecasting in real time applications. Hence, this paper makes use of ANN feature to forecast both load and availability of energy resources at microgrids in different scenarios like daily, seasonal, and yearly. The layered ANNs architecture is developed and trained with Levenberg-Marqurardt Back Propagation Algorithm. The entire design is simulated in MATLAB/Simulink. The proposed concept can be used in today's real time energy infrastructure to prevent future energy crises with improved reliability and smooth coordination among microgrids located at different areas.

关键词： Wind forecasting Artificial neural networks Wind speed Maintenance engineering Energy management Solar radiation

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Adaptive generalized predictive decoupling control for a class of MIMO nonlinear systems based on unmodeled dynamic compensation

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Kongzhi Lilun Yu Yingyong/control Theory and Applications 2012年第2期29卷 157-166页

作者： Zhang, Ya-Jun Chai, Tian-You Wang, Hong Niu, Hong The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang Liaoning 110004 China Research Center of Automation Northeastern University Shenyang Liaoning 110004 China The Control Systems Centre School of Electrical and Electronic Engineering University of Manchester M60 1QD United Kingdom Institute of System Science Northeastern University Shenyang Liaoning 110004 China

For a class of uncertain multi-input-multi-output (MIMO) discrete-time nonlinear systems with strong coupling and unstable zero-dynamics, an adaptive generalized predictive decoupling switching control method based on unmodeled dynamic compensation is proposed. It is only required that the higher order nonlinear terms of the system to satisfy a linear growth condition, rather than the global boundedness condition widely used. The analysis of stability and convergence of the adaptive control method are performed. Moreover, in designing the nonlinear generalized predictive decoupling controller, we combine the adaptive-network-based fuzzy inference system (ANFIS) training with the "one-toone mapping" technique to adaptively estimate the unmodeled dynamics, so that the universal approximation property of ANFIS can be guaranteed. Finally, simulation results demonstrate the superiority of the proposed method and validate the theoretical analysis.

关键词： Nonlinear systems

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Determining biochemical reaction network structures for kinetic polynomial models with uncertain coefficients

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AIP Conference Proceedings 2012年第1期1479卷 2427-2430页

作者： Gábor Szederkényi Z. A. Tuza Katalin M. Hangos Process Control Research Group Computer and Automation Research Institute Hungarian Academy of Sciences. Kende u. 13-17 H-1111 Budapest Hungary and Faculty of Information Technology Pázm Hungary Faculty of Information Technology Pázmány Péter Catholic University Práter u. 50/a H-1083 Budapest Hungary Process Control Research Group Computer and Automation Research Institute Hungarian Academy of Sciences. Kende u. 13-17 H-1111 Budapest Hungary and Dept. of Electrical Engineering and Informatio Hungary

A numerical method is proposed in this paper for the computation of dense and sparse reaction network structures for kinetic polynomial models with uncertain parameters represented as intervals. The problem is traced ...

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Emission model structures for an implementation on engine control units

Emission model structures for an implementation on engine co...

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作者： Sequenz, Heiko Isermann, Rolf Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University Darmstadt Germany

ISBN: (纸本)9783902661937

The number of model-based approaches in modern engine control units (ECUs) increases permanently with the increase of engine complexity. Therefore the efficient storage and the fast computation of these models is a challenging task. Due to their fast computation properties most ECUs utilize 2-dimensional grid map structures. Higher dimensional relations need then to be mapped with nested structures of several 2-dimensional grid maps. The determination of suited structures is a time-consuming task and the number of utilized 2-dimensional grid maps may be large for higher dimensional relations. Therefore in the following a grid map structure, a LOLIMOT structure, a Kernel method and an adaptive polynomial approach are compared with respect to model accuracy, computation time and required memory. Conclusions about the implementation on state of the art ECUs are given. As model output the NOx emissions of a DTH Z19 Opel CR-Diesel engine with VGT-turbocharger and exhaust gas recirculation are regarded. Model structures are presented for a global model approach comprising the engine operation point as input, and for a global-local approach predicting the output by weighting local models. © 2011 IFAC.

关键词： Exhaust gas recirculation

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Output feedback control of hypersonic vehicles based on neural network and high gain observer

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Science China(Information Sciences) 2011年第3期54卷 429-447页

作者： LI XinDong,XIAN Bin,DIAO Chen,YU YanPing,YANG KaiYan & ZHANG Yao The Tianjin Key Laboratory of process Measurement and control,School of Electrical engineering and automation,Tianjin University,Tianjin 300072,China 1. The Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and Automation Tianjin University Tianjin 300072 China

In this paper,the output feedback control problem for a genetic hypersonic vehicle is considered under the restriction that only the vehicle’s velocity and altitude are measurable. High gain observers (HGO) are utilized to provide estimation signals for unmeasurable derivatives of the vehicle’s velocity and altitude. Neural network based feedforward function is designed to compensate for model uncertainties. The proposed control design require less knowledge of the hypersonic vehicle’s dynamic model. A comprehensive stability analysis of the closed loop system under the output feedback control is carried to prove that the proposed control law yields semiglobal uniformly ultimately bounded tracking while keeping all the closed loop signals bounded. Numerical simulation results are presented to validate the proposed control design.

关键词： hypersonic vehicle nonlinear output feedback control neural network high gain observer

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Model based optimisation of a step in acceleration for a CR-Diesel engine

Model based optimisation of a step in acceleration for a CR-...

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作者： Sequenz, Heiko Mrosek, Matthias Zydek, Simon Isermann, Rolf Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University Darmstadt Germany

ISBN: (纸本)9783902661937

Due to more and more stringent emission regulations the optimisation of transient engine operation becomes necessary for future Diesel engine developments. Exemplary for the transient operation a step in acceleration pedal is investigated and optimised with respect to the engine emissions. This gives insights about the emission formation at transient driving and a benchmark for the design of open and closed-loop controls. A model structure to simulate the engine emissions and the engine torque is presented. It consists of a dynamical mean value air path model and a stationary combustion model. Thus the relevant outputs NOx, soot and torque are simulated with respect to the engine actuators. For optimisation the calibrated emission values for steady state are regarded. The actuators of the air path and the crank angle of the main injection are optimised such that the emissions follow a desired trajectory. The results are compared to a non-optimised step in acceleration and to a nonlinear closed loop control of the air path. © 2011 IFAC.

关键词： Diesel engines

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Predictive control of convex polyhedron LPV systems with Markov jumping parameters

Predictive control of convex polyhedron LPV systems with Mar...

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Chinese control and Decision Conference, CCDC

作者： Yanyan Yin Fei Liu Peng Shi Hamid Reza Karimi Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi 214122 China Department of Computing and Mathematical Sciences University of Glamorgan Pontypridd CF37 1DL United Kingdom Department of Engineering Faculty of Engineering and Science University of Agder N-4898 Grimstad Norway

The problem of receding horizon predictive control of stochastic linear parameter varying systems is discussed. First, constant coefficient matrices are obtained at each vertex in the interior of linear parameter varying system, and then, by considering semi-definite programming constraints, weight coefficients between each vertex are calculated, and the equal coefficients matrices for the time variable system are obtained. Second, in the given receding horizon, for each mode sequence of the stochastic convex polyhedron linear parameter varying systems, the optimal control input sequences are designed in order to make the states into a terminal invariant set. Outside of the receding horizon, stability of the system is guaranteed by searching a state feedback control law. Finally, receding horizon predictive controller is designed in terms of linear matrix inequality for such system. Simulation example shows the validity of this method.

关键词： Markov processes Predictive control Equations Educational institutions Programming Symmetric matrices

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Electric eddy current pick-up of turbine flow sensor and CPLD nonlinearity correction

Electric eddy current pick-up of turbine flow sensor and CPL...

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2011 International Conference on Electric Information and control engineering, ICEICE 2011

作者： Zhai, Wei-Qiang Sun, Li-Jun Liu, Xi-Bao Zhang, Tao School of Electrical Engineering and Automation Tianjin University Tianjin Key Laboratory of Process Measurement and Control China

ISBN: (纸本)9781424480395

The force due to electromagnetic pick-up can affect the performance of small pipeline turbine flow sensor. Based on electric eddy current, a new pick-up was designed for eliminating the effect of reluctance torque in traditional pick-up. The range ability of DN4mm, DN6mm and DN10mm turbine flow sensor were expanded to 101. The reliability of nonlinearity correction by software is not fully guaranteed as it was applied in bad work condition. In order to solve the problem, a method of nonlinearity correction by hardware, is that Complex Programmable Logic Device (CPLD), was put forward. It was shown by turbine flow sensor prototype experiment with electric eddy current pick-up combining CPLD hardware nonlinearity correction. DN4mm, DN6mm and DN10mm turbine flow sensor obtain the linearity 0.32%, 0.26%and 0.32% respectively in the range ability of 101. © 2011 IEEE.

关键词： Logic devices

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Gain-Scheduled H-infinity Observer Design for Nonlinear Stochastic Systems with Time-Delay and Actuator Saturation

Gain-Scheduled H-infinity Observer Design for Nonlinear Stoc...

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American control Conference

作者： Yanyan Yin Peng Shi Fei Liu Hamid Reza Karimi Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi Jiangsu 214122 P. R. China Department of Computing and Mathematical Sciences University of Glamorgan Pontypridd CF37 1DL United Kingdom Department of Engineering Faculty of Engineering and Science University of Agder N-4898 Grimstad Norway

ISBN: (纸本)9781457710957

In this paper, we propose a method for designing continuous gain-scheduled robust H_∞ observer on a class of extended stochastic nonlinear systems subject to time delay and actuator saturation. Initially, gradient linearization procedure is applied to describe such extended nonlinear systems into several model-based linear systems. Next, a robust linear H_∞ observer is designed to such linear stochastic models. Subsequently, a convex hull set is investigated and sufficient condition is derived in terms of feedback observer to determine whether a given initial condition belongs to an ellipsoid invariant set. Finally, continuous gain-scheduled approach is employed to design continuous nonlinear observers on the entire extended nonlinear jump system. A simulation example is given to illustrate the effectiveness of developed techniques.

关键词： Nonlinear stochastic system time delay Observers actuators system clock INITIAL CONDITIONS Nonlinear systems

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