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2012 6th IEEE International Conference Intelligent Systems, IS 2012

作者： Nadzinski, Gorjan Vladev, Goran Zheng, Yan Faculty of Electrical Eng. and Information Technologies SS Cyril and Methodius University Karpos 2 BB MK-1000 Skopje Macedonia College of Information Science and Engineering Institute of Control Theory and Navigation Technology Northeastern University Shenyang Liaoning 110006 China

ISBN: (纸本)9781467327824

An innovated investigation of the control problem for nonlinear discrete-time plant systems via Takagi-Sugeno fuzzy model was carried out. Firstly, nonlinear dynamic plants are represented by such a fuzzy model, and then the overall fuzzy model of nonlinear plant is transformed into a class of uncertain linear systems. Thus the stabilization problem of nonlinear plants was mapped into equivalent robust stabilization problem of uncertain linear systems with mismatched uncertainties. The robust stabilization of such uncertain systems is achieved by applying discrete-time sliding mode control approach. The stable sliding surface is designed via linear matrix inequalities to reduce the influence of mismatched uncertainties while also a sufficient condition for its existence was derived too. The synthesis design of the SMC guarantees system robust stabilization in closed loop. Chattering around the sliding surface in sliding mode control is also considerably reduced by this design. This novel technique was applied to the trailer-truck benchmark example and the essential simulation results are given to demonstrate feasibility and performance effectiveness of the proposed method. © 2012 IEEE.

关键词： Sliding mode control

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Scene Adaptive RGB-D Based Oscillation Sensing for a Multi Flexible Link Robot Arm in Unstructured Dynamic Environments

Scene Adaptive RGB-D Based Oscillation Sensing for a Multi F...

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IEEE/RSJ International Conference on Intelligent Robotics and Systems

作者： J. Malzahn A. S. Phung T. Bertram The authors are with the Institute of Control Theory and Systems Engineering Technische Universit?t Dortmund D-44221 Dortmund Germany.

ISBN: (纸本)9781467317375

The paper experimentally compares six visual oscillation sensing approaches for a three degrees of freedom flexible link robot arm with an eye-in-hand RGB-D camera. The comparison includes five representative scenarios. Based upon the results the authors propose a novel scene adaptive camera motion reconstruction scheme. The scheme adaptively selects the best approach according to the actual scene texture and depth profile. Experiments in indoor scenarios with sparse texture, poor depth profiles as well as dynamic scene contents approve the obtained signal quality to be well suited for visual vibration damping of flexible link robot arms in a great variety of frequently observed scenarios.

关键词： Multi link flexible robots visual oscillation sensing 3D computer vision

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Simulation of Nonholonomic Mechanical Systems Using Algorithmic Differentiation

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IFAC Proceedings Volumes 2012年第2期45卷 228-233页

作者： Matthias Franke Tobias Zaiczek Klaus Röbenack Frauhofer Institute Integrated Circuits Design Automation Division Zeunerstraße 38 01069 Dresden Germany Institute of Control Theory Electrical Engineering Department Technische Universität Dresden Germany

Abstract The purpose of this contribution is to introduce a new approach for simulating mechanical systems with nonholonomic constraints. The technique of algorithmic differentiation is employed together with Hamel’ s equations of motion permitting to incorporate the nonholonomic constraints directly instead of generating a system of differential-algebraic equations. To apply the proposed simulation approach, the user only needs to state the kinetic and potential energies, the nonconservative forces, and the nonholonomic constraints of the system to be simulated. The procedure is demonstrated by an illustrating example of a nonholonomic moving robot.

关键词： Mechanical system nonholonomic constraint Lagrange multiplier algorithmic differentiation quasi-velocities Hamel's equations

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Gradient Method Optimization of Penicillin Production

Gradient Method Optimization of Penicillin Production

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第24届中国控制与决策会议

作者： Matej Polka Sergej elikovsky Department of Control Engineering Faculty of Electrical Engineering Czech Technical University in PragueCzech Republic Institute of Information Theory and Automation Prague Czech Republic

A fermentation process is generally defined as a biological process containing the growth of the biomass (bacteria, yeasts) resulting from the consumption of essential substrate supplies (source of carbon, nitrogen, oxygen, etc.). The biomass growth is usually followed by the production of various products from which especially the variety of antibiotics makes the fermentation processes attractive for the industrial utilization. However, the complicated dynamics, high level of uncertainty and nonlinearity and difficult online measurement of the process variables come hand in hand with the attractivity and turn the attempts on optimal control of the fermentation process into a very delicate challenge. To tackle it, the theory of the gradient projection method has been partially adapted and fully implemented by the authors of this paper. Numerical experiments show its significantly better performance than for other known methods. Moreover, these experiments reveal an interesting "superprofile" visible for long cultivation times.

关键词： Fermentation process, penicillin, gradient method, optimization

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Improved stability conditions for unconstrained nonlinear model predictive control by using additional weighting terms

Improved stability conditions for unconstrained nonlinear mo...

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IEEE Conference on Decision and control

作者： Marcus Reble Daniel E. Quevedo Frank Allgöwer Institute for Systems Theory and Automatic Control (IST) University of Stuttgart Germany School of Electrical Engineering & Computer Science The University of Newcastle Australia

ISBN: (纸本)9781467320658

In this work, we present two unconstrained MPC schemes using additional weighting terms which allow to obtain improved stability conditions. First, we consider unconstrained MPC with general terminal cost functions. If the terminal cost is not a control Lyapunov function, but satisfies a relaxed condition, then our results yield improved estimates for a stabilizing prediction horizon. Furthermore, our analysis also allows to recover two well-known results as special cases: if the terminal cost function is chosen as zero, we recover previous conditions on the length of the prediction horizon such that stability is guaranteed; and if the terminal cost is a control Lyapunov function conform to the stage cost, stability follows independently of the length of the prediction horizon. Second, we propose to use an exponential weighting on the stage cost in order to improve the stability properties of the closed-loop. This also allows to consider local controllability assumptions in combination with a suitable terminal constraints and thereby gives a connection to the classical MPC approaches using terminal constraints.

关键词： Asymptotic stability controllability Trajectory Cost function Lyapunov methods Stability criteria

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Track-to-track fusion with asynchronous sensors and out-of-sequence tracks using information matrix fusion for advanced driver assistance systems

Track-to-track fusion with asynchronous sensors and out-of-s...

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IEEE Symposium on Intelligent Vehicle

作者： Michael Aeberhard Andreas Rauch Marcin Rabiega Nico Kaempchen Torsten Bertram Group ConnectedDrive BMW Group Research and Technology Munich Germany Institute of Control Theory and Systems Engineering Technical University Dortmund Germany

Future advanced driver assistance systems will contain multiple sensors that are used for several applications, such as highly automated driving on freeways. The problem is that the sensors are usually asynchronous and their data possibly out-of-sequence, making fusion of the sensor data non-trivial. This paper presents a novel approach to track-to-track fusion for automotive applications with asynchronous and out-of-sequence sensors using information matrix fusion. This approach solves the problem of correlation between sensor data due to the common process noise and common track history, which eliminates the need to replace the global track estimate with the fused local estimate at each fusion cycle. The information matrix fusion approach is evaluated in simulation and its performance demonstrated using real sensor data on a test vehicle designed for highly automated driving on freeways.

关键词： Sensor fusion Vehicles Radar tracking Traffic control Sensor systems Correlation

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Adaptive control of State Constrained Nonlinear Systems in Strict Feedback Form

Adaptive Control of State Constrained Nonlinear Systems in S...

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American control Conference

作者： Martin Guay Mathias Burger Department of Chemical Engineering Queens' University Kingston ON Canada Institute for Systems Theory and Automatic Control University of Stuttgart 70550 Stuttgart Germany

ISBN: (纸本)9781457710957

In this paper, we propose a systematic approach for the constructive design of adaptive control systems for nonlinear uncertain systems subject to state constraints. The analysis is restricted to a class of nonlinear systems in strict feedback form with respect to the state constraints. A novel adaptive estimation routine is employed to estimate both the unknown parameters and an approximate uncertainty sets, which is decreasing over time. The approximate uncertainty set is utilized to define a sequence of robustly controlled invariant sets which are strictly contained in the feasible set.

关键词： Uncertainty Adaptive control Nonlinear systems Robustness control systems Lyapunov methods Heuristic algorithms

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Static Diffusive Couplings in Heterogeneous Linear Networks *

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IFAC Proceedings Volumes 2012年第26期45卷 258-263页

作者： Georg S. Seyboth Dimos V. Dimarogonas Karl H. Johansson Frank Allgöwer Institute for Systems Theory and Automatic Control University of Stuttgart Pfaffenwaldring 9 70550 Stuttgart Germany ACCESS Linnaeus Center School of Electrical Engineering Royal Institute of Technology (KTH) 100 44 Stockholm Sweden

Recently, necessary and sufficient conditions for output synchronization of linear systems via diffusive couplings have been reported. In this paper, we study the case when such conditions are not satisfied and exact synchronization is impossible. In particular, we study two kinds of heterogeneous linear networks: (i) non-identical harmonic oscillators and (ii) double-integrators. We show that static diffusive couplings render heterogeneous networks of harmonic oscillators asymptotically stable. Networks of non-identical double-integrators, in contrast, are not asymptotically stable but synchronize with bounded synchronization error depending on the network topology and the heterogeneity in the agent dynamics. Numerical examples illustrate the results.

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Gradient method optimization of penicillin production

Gradient method optimization of penicillin production

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Chinese control and Decision Conference, CCDC

作者： Matej Pčolka Sergej Čelikovský Department of Control Engineering Faculty of Electrical Engineering Czech Technical University Prague Czech Republic Institute of Information Theory and Automation AS CR Prague Czech Republic

关键词： Substrates Gradient methods Mathematical model Biomass Production Biological system modeling

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Pusher reheating furnace control via fuzzy-neural model predictive control synthesis

Pusher reheating furnace control via fuzzy-neural model pred...

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2012 6th IEEE International Conference Intelligent Systems, IS 2012

作者： Stojanovski, Goran Stankovski, Mile Rudas, Imre J. Jing, Juanwei Faculty of Electrical Eng. and Information Technologies Karpos 2 SS Cyril and Methodius University Skopje MK-1000 Macedonia Institute of Intelligent Engineering Systems Óbuda University Bécsi út 96/B H-1034 Budapest Hungary College of Information Science Engineering Institute of Control Theory Navigation Technology Northeastern University Shenyang Liaoning 100006 China

ISBN: (纸本)9781467327824

A design of fuzzy model-based predictive control for industrial furnaces has been derived and applied to the model of three-zone 25 MW RZS pusher furnace at Skopje Steelworks. The fuzzy-neural variant of Sugeno fuzzy model, as an adaptive neuro-fuzzy implementation, is employed as a predictor in a predictive controller. In order to build the predictive controller the adaptation of the fuzzy model using dynamic process information is carried out. Optimization procedure employing a simplified gradient technique is used to calculate predictions of the future control actions. © 2012 IEEE.

关键词： Optimization

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