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American control Conference (ACC)

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

We consider the problem of finding a common quadratic Lyapunov function to demonstrate stability of a family of matrices which incorporate design freedoms. Generically, this can be viewed as picking a family of controller (or observer) gains so that the family of closed-loop system matrices admits a common Lyapunov function. We provide several conditions, necessary and sufficient, for various structures of matrix families. Families of matrices containing a subset of diagonal matrices invariant under the design freedoms is also considered since this is a case that occurs in many applications. Conditions for uniform solvability of the Lyapunov equations are explicitly given and involve inequalities regarding relative magnitudes of terms in the matrices. Motivating applications of the obtained results to observer and controller designs for time-varying, switched, and nonlinear systems are highlighted.

关键词： Equations Symmetric matrices Application software Lyapunov method control systems Time varying systems Nonlinear systems Robot control Laboratories Design engineering

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A high gain multiple time-scaling technique for global control of nonlinear systems

A high gain multiple time-scaling technique for global contr...

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American control Conference (ACC)

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

We consider a general high-gain scaling technique for global control of strict-feedback-like systems. Unlike previous results, the scaling utilizes arbitrary powers (instead of requiring successive powers) of the high gain parameter with the powers chosen to satisfy certain inequalities depending on system nonlinearities. The scaling induces a weak-cascading upper diagonal dominance (w-CUDD) structure on the dynamics. The analysis is based on our recent results on the w-CUDD property and uniform solvability of coupled state-dependent Lyapunov equations. The proposed scaling provides extensions in both state-feedback and output-feedback cases. The state-feedback problem is solved for a class of systems with certain ratios of nonlinear terms being polynomially bounded. The controller has a simple form being essentially linear with state-dependent dynamic gains and does not involve recursive computations. In the output-feedback case, the scaling technique is applied to the design of the observer which is then coupled with a backstepping controller. The results relax the assumption in our earlier papers on cascading dominance of upper diagonal terms. However, since the required upper diagonal cascading dominance in observer and controller contexts are dual, it is not possible to use a dual high-gain observer/controller in the proposed design preventing the bounds on uncertain functions from being of the more general form in our earlier work. A topic of further research is to examine the possibility of a scaling (perhaps utilizing more than one high gain parameter) that achieves bidirectional cascading dominance.

关键词： Nonlinear control systems control systems Nonlinear systems Backstepping Linear matrix inequalities Riccati equations Robot control Laboratories Power engineering computing Power engineering and energy

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Dynamic high gain scaling: an application to robust adaptive output feedback for feedforward systems

Dynamic high gain scaling: an application to robust adaptive...

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Asian control Conference

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

We propose an adaptive output feedback control design for global asymptotic stabilization of feedforward systems based on our recent results on dynamic high gain scaling based controller design for strict-feedback systems. The system is allowed to contain uncertain functions of all the states and the input as long as they satisfy certain bounds. Unknown parameters are allowed in the bounds assumed on uncertain functions. If the uncertain functions involve the input, then the output-dependent functions in the bounds need to be polynomially bounded. It is also shown that if the uncertain functions can be bounded by a function independent of the input, then the polynomial boundedness requirement can be relaxed. The designed controllers have a simple structure being essentially a linear feedback with state-dependent dynamic gains and do not involve any saturations or recursive computations. The observer utilized to estimate unmeasured states is similar to a Luenberger observer with dynamic observer gains. The Lyapunov functions are quadratic in state estimates, observer errors, and parameter estimation error. The stability analysis is based on our recent results on uniform solvability of coupled state-dependent Lyapunov equations. The controller provides strong robustness properties both with respect to uncertain parameters and additive disturbances. This robustness is the key to the output feedback controller design.

关键词： Robustness Output feedback Feedforward systems Observers Polynomials State estimation Robust control Programmable control Adaptive control control design

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Multi-vehicle cooperative search with uncertain prior information

Multi-vehicle cooperative search with uncertain prior inform...

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Collection of Technical Papers - AIAA Guidance, Navigation, and control Conference

作者： Zhang, Chunlei Ordóñez, Raúl Schumacher, Corey University of Dayton Dayton OH 45469-0226 United States Wright-Potterson AFB Dayton OH 45433-7531 United States Dept. of Electrical and Computer Engineering United States Control Science Division Air Force Research Laboratory United States

ISBN: (纸本)1563476703

We present a possible solution for the multi-vehicle cooperative search problem that is based on the idea of surrogate optimization to adaptively identify a terrain map on-line and use it to produce decentralized controllers yielding trajectories in a coordinated manner. We establish a discrete mathematical model for the multi-vehicle cooperative search stationary target with uncertain prior information. We reformulate the Past, Present and Predicted Future (PPP) algorithm we introduced in previous work based on the new model and propose an implementation to adapt to the new scenario to incorporate uncertain prior information. Monte Carlo simulations indicate that the new implementation achieves better performance. Moreover, the scalability of the PPP algorithm is addressed. Copyright © 2004 by the American Institute of Aeronautics and Astronautics, Inc.

关键词： Unmanned vehicles

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A new actuation approach for human friendly robot design

A new actuation approach for human friendly robot design

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IEEE International Conference on robotics and Automation (ICRA)

作者： M. Zinn O. Khatib B. Roth Department of Mechanical Engineering Design Division University of Stanford Stanford CA USA Department of Computer Science Robotics Laboratory University of Stanford Stanford CA USA

Many successful robotic manipulator designs have been introduced. However, there remains the challenge of designing a manipulator that possesses the inherent safety characteristics necessary for human-centered robotics. In this paper, we present a new actuation approach that has the requisite characteristics for inherent safety while maintaining the performance expected of modern designs. By drastically reducing the effective impedance of the manipulator while maintaining high frequency torque capability, we show that the competing design requirements of performance and safety can be successfully integrated into a single manipulation system.

关键词： Manipulators Safety Acceleration Impedance Torque Human robot interaction Service robots Brain injuries Robot sensing systems computer science

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Logo recognition using retinal coding

Logo recognition using retinal coding

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Asilomar Conference on Signals, Systems & computers

作者： K.J. Zyga J. Schroeder R. Price Sensors Division U.S. Air Force Research Laboratory USA School of Electrical and Computer Engineering University of Adelaide Australia Intelligence Analysis Group Command and Control Division Defence Science and Technology Organisation Australia

This research is an effort to model the structure and functionality of the human retina for use as an automatic identification system for logo images in document processing. Scale, rotation, noise, and distortion invariant identification is achieved using a suitable classification algorithm and a reference database. The human pulvinar is also used as a model for visual attention and logo detection within a page image. Test results show high correct identification rates, and robustness in all types of distortion.

关键词： Retina Humans Australia Intelligent sensors Image databases Testing Optical filters Photoreceptors Equations Transfer functions

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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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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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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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Identifying strength of boards using mechanical modeling and a Weibull-based feature

Identifying strength of boards using mechanical modeling and...

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IEEE Conference on control Technology and Applications (CCTA)

作者： A.A. Saravi P.D. Lawrence F. Lam 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

The most accurate way of identifying the strength of lumber requires destructive testing which is clearly not useful for production of lumber. An intelligent mechanics-based lumber grading system was developed to provide a better estimation of the strength of a board nondestructively. This system processed X-ray-extracted geometric features (of 1080 boards that eventually underwent destructive strength testing) by using physical model of lumber based on finite element methods (FEM) to generate associated stress fields. The stress fields were then fed to a feature-extracting-processor which produced seven strength predicting features. The best strength predicting features were determined from the coefficient of determination (r/sup 2/) between the features and actual strengths of the boards. A coefficient of determination of 0.4732 was achieved by using a Weibul-based feature and using a linear transformation of the same feature to predict the estimated strength, respectively.

关键词： Stress X-ray imaging Robot control Testing Production Solid modeling Intelligent systems Humans Neural networks Councils

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