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Optimizing Supervision and control for Industrial Furnaces: Predictive control Based Design

IFAC Proceedings Volumes 2004年第19期37卷 17-28页

作者： Georgi M. Dimirovski A. Talha Dinibütün Miomir K. Vukobratovic J. Zhao SS Cyril and Methodius University Faculty of Electrical Engineering MK-1000 Skopje Republic of Macedonia Dogus University Computer Engineering Department Faculty of Engineering Acibadem Zeamet Sk. 21 Kadikoy TR-34722 Istanbul Turkey Institute “Mihailo Pupin” Centre of Robotics and Flexible Automation 11000 Belgrade Serbia and Montenegro Northeastern University School of Information Science and Engineering Institute of Control Theory Shenyang Liaoning 110004 P.R. of China

A systems re-engineering technique to integrated control and supervision for applications to industrial multi-zone furnaces has been elaborated by using known theories on generalized predictive control and nonlinear programming. This paper presents the derivation of optimizing equations and inequalities. The design is based on the use of general predictive control to provide optimized set-points under the presumption a well designed regulatory control was implemented at the executive level. Digital implementation of control functions are sought within standard computer process control platform for practical engineering and maintenance reasons.

关键词： Complex time-delay processes generalized predictive control integrated control and supervision optimization set-point control

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Vehicle model aided inertial navigation

Vehicle model aided inertial navigation

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2003 IEEE International Conference on Intelligent Transportation Systems, ITSC 2003

作者： Ma, Xin Sukkarieh, Salah Kim, Jong-Hyuk Department of Control Science and Engineering Shandong University China Australian Centre for Field Robotics School of Aerospace Mechanical and Mechatronic Engineering University of Sydney SydneyNSW2006 Australia

ISBN: (纸本)0780381254

This paper studies the possibility of improving the accuracy of a low-cost strapdown inertial navigation system mounted on a land vehicle by using a vehicle kinematic model. The inertial navigation system is aided with virtual position measurements, which are predicted by a vehicle kinematic model along with virtual velocity measurements. This data is obtained from the non-holonomic constraints that govern land vehicle motion on a surface. Furthermore, the updated heading information obtained from the INS is used to refine the vehicle kinematic model. Analytic analysis and covariance simulation are carried out for the observability analysis of the aided inertial navigation system. Simulation results prove that the accuracy of the low-grade inertial navigation system aided by a vehicle kinematic model can be considerably improved. The strategies proposed in this paper can be used as a backup navigation loop during outages of CPS for an extended amount of time with the navigation error noticeably bounded. Finally, the redundancy and the integrity of the whole navigation system are also further enhanced. © 2003 IEEE.

关键词： Inertial navigation systems

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Implementation of a Neural Network Based System for Estimating the Strength of a Board Using Mixed Signals

Implementation of a Neural Network Based System for Estimati...

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2003 IEEE Pacific Rim Conference on Communications Computers and Signal Processing (PACRIM 2003)

作者： Saboksayr, Hossein Saravi, Albert Lawrence, Peter D. Lam, Frank IEEE Control System Society Vancouver BC Canada Robotics and Control Laboratory Department of Electrical Engineering University of British Columbia Vancouver BC Canada Department of Wood Science University of British Columbia Vancouver BC Canada

An intelligent lumber grading system was developed to provide a new way for estimating the strength of a board by posing the estimation problem as an empirical learning problem. This system processed the X-Ray image, extracted geometric features (of 1000 boards that eventually underwent destructive strength testing), and predicted the strength of the lumber by using a neural network. The X-Ray image was passed through a threshold filter to separate the knots based on the fact that a denser knot produces a local maximum (as a rounded protrusion in an otherwise almost flat density surface) of the x-ray image. Each knot was modeled by a three-dimensional-cone with seven parameters. Information on all the detected knots such as volume, and knot-area-ratio were fed to a processor to generate 16 geometrical features (such as;the average of knot area ratio, and the number of knots detected in each board) which characterize each board. Then by using back-propagation as the training method, cross correlation as the measure of accuracy, and actual strength of a thousand boards as the empirical data set, a neural network was trained to estimate the strength of each board. The learning system consisted of three layers, with 1, 5, 16 neurons in output, hidden and input layer respectively. Ten-fold cross validation was used to produce an unbiased accuracy of the estimation problem. The learning and testing sets comprised of 900 and 100 boards respectively. By repeating the learning and testing for ten times and averaging the results, a coefficient of determination of 0.4059 was reached in this study for using X-Ray images alone. The same methodology was applied to MOE (Modulus of Elasticity) and a coefficient of determination of 0.56 was reached. The results were improved by fusing the X-Ray image and MOE using a learning system consisting of three layers, with 1, 5, 40 neurons in output, hidden and input layer respectively. Ten-Fold cross validation resulted in a coefficient of

关键词： Intelligent control

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OPTIMIZING THE SUBDIVISION OF ELEMENTS IN DISCONTINUITY MESHING FOR HIERARCHICAL RADIOSITY

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International Journal on Artificial Intelligence Tools 2003年第4期12卷 395-411页

作者： IOANNIS A. PANTAZOPOULOS SPYROS G. TZAFESTAS Intelligent Robotics and Automation Laboratory Signals Control and Robotics Division Electrical and Computer Engineering Department National Technical University of Athens Zographou Athens Greece

This paper presents a new topological structure for use in the context of hierarchical radiosity combined with discontinuity meshing. This is most useful for a new strategy adopted for subdividing the elements of a scene consisting of convex polygons. The subdivision is done in a local optimization manner keeping the aspect ratios of produced polygons low. The generated meshes give high visual accuracy.

关键词： Hierarchical radiosity discontinuity meshing mesh pre(post)-processing multigriding aspect-ratio

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Motion control for mobile robot obstacle avoidance and navigation: A fuzzy logic-based approach

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Systems Analysis Modelling Simulation 2003年第12期43卷 1625-1637页

作者： Zavlangas, Panagiotis G. Tzafestas, Spyros G. Control and Robotics Department School of Electrical and Computer Engineering National Technical University of Athens Zografou 15773 Athens Greece

One of the ultimate goals of mobile robotics research is to build robots that can safely carry out missions in hazardous and populated environments. Most of today's commercial mobile devices scale poorly along this dimension. Their motion planning relies on accurate, static models of the environments, and therefore they often fail their mission if humans or other unpredictable obstacles block their path, To build autonomous mobile robots one has to build systems that can perceive their environments, react to unforeseen circumstances, and plan dynamically in order to achieve their mission. Thus, the objective of the motion planning and control problem is to find collision-free trajectories, in static or dynamic environments containing some obstacles, between a start and a goal configuration. It has attracted much research in recent years. In this context the term control has a broad meaning that includes many different controls, such as low-level motor control, and behaviour control, where behaviour represents many complicated tasks, like obstacle avoidance and goal seeking. This article describes an intelligent motion planning and navigation system for omnidirectional mobile robots based on fuzzy logic. Owing to its simplicity and hence its short response time, the fuzzy navigator is especially suitable for on-line applications with strong real-time requirements. On-line planning is an on-going activity. The planner receives a continuous flow of information about occurring events and generates new commands in response to the incoming events, while previously planned motions are being executed. The fuzzy-rule-base of the proposed system combines the repelling influence, which is related to the distance and the angle between the robot and nearby obstacles, with the attracting influence produced by the distance and the angular difference between the actual direction and position of the robot and the final configuration, to generate actuating commands for the mobile pla

关键词： Mobile robots

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Implementation of a neural network based system for estimating the strength of a board using mixed signals

Implementation of a neural network based system for estimati...

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IEEE Pacific Rim Conference on Communications, Computers and Signal Processing

作者： H. Saboksayr A. Saravi P.D. Lawrence F. Lam IEEE Control System Society Vancouver Canada Robotics and Control Laboratoryratory Department of Electrical and Computer Engineering University of British Columbia Vancouver Canada Robotics and Control Laboratory Department of Electrical and Computer Engineering University of British Columbia Vancouver Canada Department of Wood Science University of British Columbia Vancouver Canada

An intelligent lumber grading system was developed to provide a new way for estimating the strength of a board by posing the estimation problem as an empirical learning problem. This system processed the X-ray image, extracted geometric features (of 1000 boards that eventually underwent destructive strength testing), and predicted the strength of the lumber by using a neural network. The X-ray image was passed through a threshold filter to separate the knots based on the fact that a denser knot produces a local maximum (as a rounded protrusion in an otherwise almost flat density surface) of the X-ray image. Each knot was modeled by a three-dimensional-cone with seven parameters. Information on all the detected knots such as volume, and knot-area-ratio were fed to a processor to generate 16 geometrical features (such as; the average of knot area ratio, and the number of knots detected in each board), which characterize each board. Then by using back-propagation as the training method, cross correlation as the measure of accuracy, and actual strength of a thousand boards as the empirical data set, a neural network was trained to estimate the strength of each board. The learning system consisted of three layers, with 1, 5, 16 neurons in output, hidden and input layer respectively. Ten-fold cross validation was used to produce an unbiased accuracy of the estimation problem. The learning and testing sets comprised of 900 and 100 boards respectively. By repeating the learning and testing for ten times and averaging the results, a coefficient of determination of 0.4059 was reached in this study for using X-ray images alone. The same methodology was applied to MOE (modulus of elasticity) and a coefficient of determination of 0.56 was reached. The results were improved by fusing the X-ray image and MOE using a learning system consisting of three layers, with 1, 5, 40 neurons in output, hidden and input layer respectively. Ten-Fold cross validation resulted in a coefficient o

关键词： Neural networks X-ray imaging Feature extraction Learning systems Neurons Intelligent systems System testing Filters Character generation Elasticity

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A dual high gain controller for the uncertain generalized output-feedback canonical form with appended dynamics driven by all states

A dual high gain controller for the uncertain generalized ou...

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American control Conference (ACC)

作者： P. Krishnamurthy F. Khorrami Control Robotics Research Laboratory(CRRL)Department of Electncal and Computer Engineering Polytechnic University Brooklyn NY USA

In this paper, we propose a global high gain scaling based observer/controller for nonlinear systems with appended input-to-state stable (ISS) dynamics which are allowed to have finite nonlinear gains from all system states. This represents a significant generalization from existing results which require the appended dynamics to be ISS with respect to the output i.e., require the gains from other states to be zero. The restriction on the appended ISS dynamics imposed in previous results is due to the form of the Lyapunov functions generated in the backstepping design utilized which prevents gains from states of appended dynamics to system states other than the output to be effectively assigned. The proposed design utilizes the dual architecture of a high gain observer and controller with the underlying state scaling being dynamically output-dependent. The proposed observer/controller structure provides a globally asymptotically stabilizing output-feedback solution. Furthermore, time varying nonlinear parametric uncertainty is allowed to occur coupled with unmeasured states in the system dynamics.

关键词： Nonlinear dynamical systems Lyapunov method control systems Nonlinear control systems Robot control Laboratories Nonlinear systems Backstepping Uncertainty Couplings

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Solution to the general robust strictly positive real synthesis problem for polynomial segments

Solution to the general robust strictly positive real synthe...

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2003 European control Conference, ECC 2003

作者： Yu, Wensheng Wang, Long Ackermann, Jürgen Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing100080 China Center for Systems and Control Department of Mechanics and Engineering Science Peking University Beijing100871 China Robust Control Group Institute of Robotics and Mechatronics German Aerospace Center DLR-Oberpfaffenhofen Postfach 1116 WesslingD-82230 Germany

For any two n-th order polynomials a(s) and b(s), the Hurwitz stability of their convex combination is necessary and sufficient for the existence of a polynomial c(s) such that c(s)/a(s) and c(s)/b(s) are both strictl... 详细信息

ISBN: (纸本)9783952417379

关键词： Polynomials

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Adaptive partial-state feedback control for induction motors

Adaptive partial-state feedback control for induction motors

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American control Conference (ACC)

作者： P. Krishnamurthy F. Khorrami Control Robotics Research Labomtory Department of Electrical and Computer Engineering Six Metrotech Center Polytechnic University Brooklyn NY USA

In this paper, a nonlinear adaptive dynamic controller is designed for velocity and flux magnitude tracking of induction motors. The control design is a partial-state feedback design that utilizes rotor velocity and stator current measurements. Rotor position and flux measurements are not utilized for feedback. Further more, an adaptive approach is followed to compensate for uncertainty in the mechanical parameters (inertia, friction, and load torque) and the rotor resistance. The only information required about these parameters is a lower bound on the rotor resistance. The designed controller has dynamic order 12 and achieves asymptotic tracking of the flux magnitude trajectory. Under a persistency of excitation condition, asymptotic tracking of the flux magnitude trajectory is also obtained.

关键词： Programmable control Adaptive control Feedback control Induction motors Rotors Trajectory Velocity control control design Stators Current measurement

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Real-time optimized robot trajectory planning with jerk 7

Real-time optimized robot trajectory planning with jerk

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7th IFAC Symposium on Robot control, SYROCO 2003

作者： Voss, Gabor Lantos, Béla Payandeh, Shahram Budapest University of Technology and Economics Department of Control Engineering and Information Technology Pázmány Péter sétány 1/D BudapestH-1117 Hungary Simon Fraser University Experimental Robotics Laboratory School of Engineering Science BurnabyBCV5A 1S6 Canada

In several robot applications the spatial trajectories of the robot motion are defined by the user, and must be tracked precisely. Executing the prescribed spatial trajectories of the motion of a robot, the dynamic properties of the robot can be considered. The maximum velocity, acceleration and jerk of each joint of the robot determine limits of the motion. Therefore, the real-time trajectory generation should consider all of these limits to produce near time-optimal motion. The proposed method of this paper is an optimized version of a jerk switching trajectory planning algorithm (MSRS), which considers the maximum joint velocity, acceleration and jerk properties. Modification of corner points at the end of the list or adding new ones can be performed real-time. Copyright © IFAC Robot control, Wroclaw, Poland, 2003.

关键词： Robot applications

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