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2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)

作者： Krishna Kumar Narayanan Luis Felipe Posada Frank Hoffmann Torsten Bertram Institute of Control Theory and Systems Engineering Technische Universit(a)t Dortmund44227DortmundGermany

The design of visual robotic behaviors constitutes a substantial challenge. It requires to draw meaningful relationships and constraints between the acquired visual perception and the geometry of the environment both empirically and programmatically. This contribution proposes a novel robot learning framework to classify and acquire scenario specific autonomous behaviors through demonstration. During demonstration, robocentric 3D range and omnidirectional images are recorded as training instances of typical robot navigation situations pertaining to different contexts in multiple indoor scenarios. A programming by demonstration approach generalizes the demonstrated trajectories to a general mapping between visual features extracted from the omnidirectional image onto a corresponding robot motion. The approach is able to distinguish among different traversing scenarios and further identifies the best matching context within the scenario to predict an appropriate robot motion. As a comparison to context matching, the behaviors are trained by means of an artificial neural network and its generalization ability is evaluated against the former. The experimental validation on the mobile robot indicates that the acquired visual behavior is robust and generalizes meaningful actions beyond the specific environments and scenarios presented during training.

关键词： Robots Trajectory Context Training Visualization Collision avoidance Artificial neural networks

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On state-constrained control of a CSTR

On state-constrained control of a CSTR

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作者： Bayer, Florian Bürger, Mathias Guay, Martin Allgöwer, Frank Institute for Systems Theory and Automatic Control University of Stuttgart Pfaffenwaldring 9 70550 Stuttgart Germany Department of Chemical Engineering Queen's University Kingston ON K7L 3N6 Canada

ISBN: (纸本)9783902661937

In this note, we study the problem of multiple hard output constraints imposed on a continuous stirred tank reactor (CSTR) subject to external disturbances. Constraints on the concentration and on the temperature are considered. We show, analytically and with simulations, that there are critical combinations of constraints, where robust constraint satisfaction cannot be guaranteed. As a consequence violation of at least one constraint has to be allowed. © 2011 IFAC.

关键词： Robust control

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Connection profile robustness in a heterogeneous network of piecewise affine FitzHugh-Nagumo models

Connection profile robustness in a heterogeneous network of ...

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50th Annual Conference on Society of Instrument and control Engineers, SICE 2011

作者： Kashima, Kenji Papachristodoulou, Antonis Allgöwer, Frank Graduate School of Information Science and Engineering Tokyo Institute of Technology Tokyo Japan Department of Engineering Science University of Oxford Parks Road Oxford OX1 3PJ United Kingdom Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart Germany

ISBN: (纸本)9784907764395

FitzHugh-Nagumo is one of the best known nonlinear neuronal models in mathematical physiology. In particular, spatio-temporal forms of this model have been used for modeling oscillatory behavior in living organisms such as the behavior of cardiac pacemaker cells. In this paper, we investigate the stability of their spatially discretized form, that is, diffusively coupled large-scale networks of piecewisely affine approximated FitzHugh-Nagumo models. Scalable criteria for ultimate boundedness are given taking connection profile (coupling strength, delay length, subsystem heterogeneity) robustness into account. This result is accomplished through a linear multi-agent system perspective for a class of piecewise affine systems. © 2011 SICE.

关键词： Large scale systems

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Offline NMPC for continuous-time systems using sum of squares

Offline NMPC for continuous-time systems using sum of square...

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2011 American control Conference (ACC)

作者： Frederik Deroo Christoph Maier Christoph Bohm Frank Allgower Institute of Automatic Control Engineering (LSR) Technische Universität München Germany Allgöwer Institute for Systems Theory and Automatic Control (IST) University of Stuttgart Germany

An offline nonlinear model predictive control (NMPC) approach for continuous time nonlinear systems subject to input and state constraints is presented. The approach deals with nonlinear systems which can be represented by polynomial parameter-varying systems. Since the applicability of NMPC is often limited by the speed at which an optimization problem can be solved online, we propose an NMPC scheme with drastically reduced online computational burden. The basic idea involves the offline computation of nested invariant sets and associated feedback laws by solving a convex optimization problem subject to sum of squares (SOS) constraints via semidefinite programming (SDP). Online, a search algorithm is executed to determine the feedback law suitable for the current state. The resulting offline NMPC controller guarantees stability and constraint satisfaction. Its applicability and effectiveness is shown by means of simulation of an example system.

关键词： Polynomials Optimization Nonlinear systems Trajectory Symmetric matrices Lyapunov methods

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A Lie Bracket Approximation for Extremum Seeking Vehicles

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IFAC Proceedings Volumes 2011年第1期44卷 11393-11398页

作者： Miloš S Stanković Hans-Bernd Dürr Karl Henrik Johansson Institute for Systems Theory and Automatic Control University of Stuttgart Germany ACCESS Linnaeus Center School of Electrical Engineering Royal Institute of Technology (KTH) 100-44 Stockholm Sweden

Abstract In this paper we propose a novel methodology for the analysis of autonomous vehicles seeking the extremum of an arbitrary smooth nonlinear map in the plane. By interpreting the extremum seeking schemes as input-affine systems with periodic excitations and by using the methodology of Lie brackets, we calculate a simplified system which approximates the qualitative behavior of the original one better than existing methods. By examining this approximate Lie bracket system, we are able to directly derive properties of the original one. Thus, by showing that the Lie bracket direction is directly related to the unknown gradient of the objective function we prove global uniform practical asymptotic stability of the extremum point for vehicles modeled as single integrators and non-holonomic unicycles. We illustrate the proposed method through simulations.

关键词： Extremum Seeking Autonomous Mobile Robots Stability Nonlinear control systems

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Event-based NMPC for Networked control systems over UDP-like Communication Channels

Event-based NMPC for Networked Control Systems over UDP-like...

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2011 American control Conference (ACC)

作者： Paolo Varutti Rolf Findeisen Laboratory for Systems Theory and Automatic Control Institute for Automation Engineering Otto-von-Guericke University of Magdeburg Magdeburg Germany

Networked controlled systems have recently received attention from the industry since they allow for flexibility and cost reduction. However, due to the fact that communication media can be subject to random delays, packet dropouts, jitters and other uncertainties, destabilization of the closed loop system can occur. Model predictive control has demonstrated to be a valid solution to cope with these issues. On the other hand, it typically relies on TCP-like (or connection oriented) protocols, i.e. either the received or the lost information is acknowledged. In this work, we propose an event-based model predictive control algorithm for nonlinear continuous time systems subject to state and input constraints which is based on UDP-like communication. We show that without the use of any acknowledgment or error message we can derive a compensation algorithm, which used in combination with the controller, under mild conditions, guarantees closed loop stability. The solution is applied to a continuous stirred tank reactor where an exothermic irreversible reaction takes place. The simulations show the effectiveness of the presented algorithm.

关键词： Loss measurement Delay Stability analysis Predictive models Asymptotic stability Prediction algorithms Closed loop systems

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The application of BP Neural Network based on improved PSO in BF temperature forecast

The application of BP Neural Network based on improved PSO i...

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2nd Annual Conference on Electrical and control engineering, ICECE 2011

作者： Wang, Hongjun Li, Dexiong Zhao, Zhuoqun Qi, Huijuan Liu, Lina Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Tianjin University of Technology Nankai District Tianjin 300191 China HNV College of Mechanical and Vehic Engineering Changsha 410082 China Shijiazhuang Institute of Railway Technology Qiaodong District Shijiazhuang 050041 China

ISBN: (纸本)9781424481637

The BP network has the disadvantages such as low learning efficiency, low speed of convergence, easily falling into the local minimum state, poor ability to adapt, ect. For PSO algorithm, it is fast for convergence, especially at the initial stage, simple for the computing, and is easy to implement. Compared with the genetic algorithms, it does have not the complex operations of hybrid codecs, mutation, so it is a good optimization algorithm. However, PSO algorithm also has some shortcomings it is more and more slow for convergence rate at the late evolution of the algorithm. In this paper, a new BP Neural Network based on improved Particle Swarm Optimization (PSO) is proposed. The convergence speed of this algorithm and the capacity of searching global extremum is increased through adjusting the adaptive capacity of learning factor. The simulation results illustrate that the improved PSO is superior to the standard BP algorithm and particle swarm optimization. © 2011 IEEE.

关键词： Neural networks

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Tube MPC Scheme based on Robust control Invariant Set with Application to Lipschitz Nonlinear systems

Tube MPC Scheme based on Robust Control Invariant Set with A...

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IEEE Conference on Decision and control

作者： Shuyou Yu Hong Chen Frank Allgower Institute of Systems Theory and Automatic Control University of Stuttgart Germany State Key Laboratory of Automobile Dynamic Simulation and Department of Control Science and Engineering Jilin University PR China

ISBN: (纸本)9781612848006

The paper presents a tube model predictive control (MPC) scheme of continuous-time nonlinear systems based on robust control invariant set. The optimization problem considered has a general cost functional rather than the quadratic one. The scheme has the same online computational burden as the standard MPC with guaranteed nominal stability. Robust stability, as well as recursive feasibility, is guaranteed if the optimization problem is feasible at the initial time instant. Furthermore, an optimization based control scheme is proposed, which inherits the robust properties of the tube MPC scheme. The related optimization problem is solved only at the initial time instant. In particular, we consider a scheme to obtain robust control invariant set for Lipschitz nonlinear systems, and show the effectiveness of the proposed schemes by a simple example.

关键词： Robust control Scheme Invariant COHERENT TUBE MODEL

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Distributed Positioning of Autonomous Mobile Sensors with Application to Coverage control

Distributed Positioning of Autonomous Mobile Sensors with Ap...

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2011 American control Conference (ACC)

作者： Hans-Bernd Durr Milos S. Stankovic Karl Henrik Johansson Institute for Systems Theory and Automatic Control University of Stuttgart Germany ACCESS Linnaeus Center School of Electrical Engineering Royal Institute of Technology Stockholm Sweden

We consider problems in multi-agent systems where a network of mobile sensors needs to self-organize such that some global objective function is maximized. To deal with the agents' lack of global information we approach the problem in a game-theoretic framework where agents/players are only able to access local measurements of their own local utility functions whose parameters and detailed analytical forms may be unknown. We then propose a distributed and adaptive algorithm, where each agent applies a local extremum seeking feedback adopted to its specific motion dynamics, and prove its global practical stability, implying that the agents asymptotically reach a configuration that is arbitrary close to the globally optimal one. For the stability analysis we introduce a novel methodology based on a Lie bracket trajectory approximation and combine it with a potential game approach. We apply the proposed algorithm to the sensor coverage problem and solve it in a distributed way where the agents do not need any a priori knowledge about the distribution of the events to be detected and about the detection probabilities of the individual agents. The proposed scheme is illustrated through simulations.

关键词： Sensors Games Asymptotic stability Trajectory Mathematical model Stability analysis Convergence

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Event-based NMPC for networked control systems over UDP-like communication channels

Event-based NMPC for networked control systems over UDP-like...

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作者： Varutti, Paolo Findeisen, Rolf Laboratory for Systems Theory and Automatic Control Institute for Automation Engineering Otto-von-Guericke University Magdeburg Germany Intl. Max Planck Res. Sch. for Analysis Des. and Optimization in Chem. and Biochem. Proc. Eng. Magdeburg Germany

ISBN: (纸本)9781457700804

关键词： Model predictive control

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