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2nd IFAC Conference on Embedded Systems, computer Intelligence and Telematics, CESCIT 2015

作者： Precup, Radu-Emil Petriu, Emil M. Radac, Mircea-Bogdan Voisan, Emil-Ioan Dragan, Florin Department of Automation and Applied Informatics Politehnica University of Timisoara Bd. V. Parvan 2 Timisoara300223 Romania School of Electrical Engineering and Computer Science University of Ottawa 800 King Edward OttawaONK1N 6N5 Canada

This paper suggests the application of adaptive Charged System Search (CSS) algorithms to the optimal path planning (PP) of multiple mobile robots. An off-line adaptive CSS-based PP approach is proposed and applied to holonomic wheeled platforms in static environments. The adaptive CSS algorithms solve the optimisation problems that aim the minimisation of objective functions (o.f.s) specific to PP and expressed as the weighted sum of four functions that target separate PP objectives. A penalty term is added in certain situations in the first step of the PP approach. The specific features of the adaptive CSS algorithms are the adaptation of the acceleration, velocity, and separation distance parameters to the iteration index, and the substitution of the worst charged particles' fitness function values and positions with the best performing particle data. The fitness function in the adaptive CSS algorithms corresponds to the o.f., and the search space and agents (charged particles) in the adaptive CSS algorithms correspond to the solution space and to the mobile robots, respectively. A case study and experiments are included validate the new adaptive CSS-based PP approach and to compare it with nonadaptive CSS-, Particle Swarm Optimization-and Gravitational Search Algorithm-based PP approaches. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Motion planning

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Data-driven optimal model-free control of twin rotor aerodynamic systems

Data-driven optimal model-free control of twin rotor aerodyn...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Raul-Cristian Roman Mircea-Bogdan Radac Radu-Emil Precup Emil M. Petriu Department of Automation and Applied Informatics Politehnica University of Timisoara Timisoara Romania School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada

This paper proposes data-driven Model-Free Control (MFC) algorithms for Multi Input-Multi Output (MIMO) twin rotor aerodynamic systems. A discrete-time formulation of the algorithms is given in the framework of a MIMO control system structure with azimuth and pitch position control loops. An optimal design approach of the MIMO MFC algorithms is proposed using a Linear Quadratic Regulator formulation. The sensitivity of the new MFC structure with respect to parametric variations of the aerodynamic system is checked against two additional structures that are also optimally designed. The case study also reveals how the sampling time influences the control system performance.

关键词： MIMO Sensitivity Aerodynamics Process control Optimization Algorithm design and analysis Trajectory

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Model predictive control solution for magnetic levitation systems

Model predictive control solution for magnetic levitation sy...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Claudia-Adina Bojan-Dragos Alexandra-Iulia Stinean Radu-Emil Precup Stefan Preitl Emil M. Petriu Department of Automation and Applied Informatics Politehnica University of Timisoara Timisoara Romania School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada

The paper presents aspects related to the design and implementation of a cascade control solution (CCS), which is tested on laboratory equipment meant for the position control of a ferromagnetic sphere in a Magnetic Levitation System with Two Electromagnets (MLS2EM). The nonlinear mathematical model (MM) of the MLS2EM is derived on the basis of the first principles equations with experimentally identified parameters. This MM is next linearized at two operating points. The CCS includes a state feedback controller in the inner loop and a model predictive controller in the outer loop. Experimental results are given in order to validate the proposed CCS and to illustrate the performance of the position control system expressed as very good dynamics and zero steady-state control error.

关键词： Electromagnets State feedback Mathematical model Magnetic materials Photonic crystals Magnetic levitation

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Implementation of evolving fuzzy models of a nonlinear process

Implementation of evolving fuzzy models of a nonlinear proce...

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International Conference on informatics in Control, Automation and Robotics (ICINCO)

作者： Radu-Emil Precup Emil-Ioan Voisan Emil M. Petriu Mircea-Bogdan Radac Lucian-Ovidiu Fedorovici Department of Automation and Applied Informatics Politehnica University of Timisoara Timisoara Romania School of Electrical Engineering and Computer Science University of Ottawa Ottawa ON Canada

This paper presents details on the implementation of evolving Takagi-Sugeno-Kang (TSK) fuzzy models of a nonlinear process represented by the pendulum dynamics in the framework of the representative pendulum-crane systems. The pendulum angle is the output variable of the TSK fuzzy models that are obtained by online identification. The rule bases and the parameters of the TSK fuzzy models are continuously evolved by an online identification algorithm (OIA) that adds new rules with more summarization power and modifies the existing rules and parameters. The OIA is associated with an input selection algorithm that guides the modelling in terms of ranking the inputs according to their importance factors. Three TSK fuzzy models evolved by the OIA are exemplified. The performance of the new evolving TSK fuzzy models is illustrated by experimental results conducted on pendulum-crane laboratory equipment.

关键词： Input variables Adaptation models Computational modeling Heuristic algorithms Classification algorithms Takagi-Sugeno model Cranes

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Optimal motion prediction using a primitive-based model-free iterative control approach for crane systems

Optimal motion prediction using a primitive-based model-free...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Mircea-Bogdan Radac Radu-Emil Precup Emil M. Petriu Department of Automation and Applied Informatics Politehnica University of Timisoara Timisoara Romania School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada

This paper suggests an optimal behavior prediction mechanism for a control system, using previously learned solutions to simple tasks called primitives. The optimality of the behavior is formulated as a reference trajectory tracking problem. The primitives are stored in a library of pairs of reference input/controlled output signals. The reference input primitives are optimized in a Model-Free Iterative Learning Control framework without using knowledge of the controlled process. The new complex trajectories to be tracked are decomposed into the output primitives regarded as basis functions. The optimal reference input fed to the control system in order to track the desired new trajectory is then recomposed from the reference input primitives. The efficiency of this approach is demonstrated on a case study concerning the position control of a two-axis positioning mechanism in a laboratory crane system application.

关键词： MIMO Trajectory Approximation methods Optimization Process control Cranes

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Takagi-Sugeno PD+I fuzzy control of processes with variable moment of inertia

Takagi-Sugeno PD+I fuzzy control of processes with variable ...

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IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA)

作者： Alexandra-Iulia Stînean Claudia-Adina Bojan-Dragos Radu-Emil Precup Stefan Preitl Emil M. Petriu Department of Automation and Applied Informatics Politehnica University of Timisoara Timisoara Romania School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada

The paper presents aspects related to the design and implementation of a Takagi-Sugeno (TS) proportionalderivative (PD) + integral (I) fuzzy controller for processes with variable moment of inertia. A two-step design method for the TS PD+I fuzzy controller applied to position control systems is proposed. The first step concerns the Extended Symmetrical Optimum method-based tuning of the parameters of linear PID controllers organized in a parallel scheme. The second step deals first with the fuzzification of the linear PD component in the PID controller scheme resulting in the TS PD fuzzy block (TS PD FB). The modal equivalence principle is next employed to tune the parameters of TS PD FB that operates as a bump-less interpolator between separately tuned PD controllers placed in the rule consequents. The presentation is focused on the position control of a representative mechatronics application with variable moment of inertia, namely the laboratory equipment built around the Model 220 Industrial Plant Emulator. Experimental results are given to validate the PID controllers and design method in several case studies. The comparison of TS PD+I fuzzy controller versus PID controllers is supported by experimental results.

关键词： PD control Niobium Process control Design methodology Mathematical model Pulleys

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Backtracking Search Optimization Algorithm-based approach to PID controller tuning for torque motor systems

Backtracking Search Optimization Algorithm-based approach to...

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Annual IEEE Systems Conference

作者： Radu-Emil Precup Alexandra-Dina Balint Mircea-Bogdan Radac Emil M. Petriu Department of Automation and Applied Informatics Politehnica University of Timisoara Timisoara Romania School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada

This paper suggests the Backtracking Search Optimization Algorithm (BSOA)-based tuning of the parameters of proportional-integral-derivative (PID) controllers for a pancake direct current (DC) torque motor systems. These motors are important in the framework of Diesel engine exhaust gas recirculation valves in automotive applications. The BSOAs solve optimization problems that minimize objective functions expressed as the weighted sum of overshoot plus the integral of squared control error. The parameters of the PID controllers are the elements of the vector variables of the objective functions. The impact of the parameter that controls the amplitude of the search direction matrix is analyzed in terms of a digitally simulated case study that performs the shaft angle control.

关键词： Tuning Optimization Linear programming Torque Sociology Statistics Control systems

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Distributed submodular maximization

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2016年第1期17卷

作者： Kevin Murphy Bernhard Schölkopf Baharan Mirzasoleiman Amin Karbasi Rik Sarkar Andreas Krause Google MPI for Intelligent Systems Department of Computer Science ETH Zurich Zurich Switzerland School of Engineering and Applied Science Yale University New Haven Department of Informatics University of Edinburgh Edinburgh United Kingdom

Many large-scale machine learning problems-clustering, non-parametric learning, kernel machines, etc.-require selecting a small yet representative subset from a large dataset. Such problems can often be reduced to maximizing a submodular set function subject to various constraints. Classical approaches to submodular optimization require centralized access to the full dataset, which is impractical for truly large-scale problems. In this paper, we consider the problem of submodular function maximization in a distributed fashion. We develop a simple, two-stage protocol GREEDI, that is easily implemented using MapReduce style computations. We theoretically analyze our approach, and show that under certain natural conditions, performance close to the centralized approach can be achieved. We begin with monotone submodular maximization subject to a cardinality constraint, and then extend this approach to obtain approximation guarantees for (not necessarily monotone) submodular maximization subject to more general constraints including matroid or knapsack constraints. In our extensive experiments, we demonstrate the effectiveness of our approach on several applications, including sparse Gaussian process inference and exemplar based clustering on tens of millions of examples using Hadoop.

关键词： approximation algorithms distributed computing greedy algorithms map-reduce submodular functions

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(1,7,4) Data hiding scheme for searching in hidden text with automata

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Vietnam Journal of computer Science 2015年第4期2卷 257-265页

作者： Le Quang Hoa Nguyen Huy Truong Cheonshik Kim Ching-Nung Yang School of Applied Mathematics and Informatics Hanoi University of Science and Technology Hanoi Vietnam Department of Digital Media Engineering Anyang University Anyang Republic of Korea Department of Computer Science and Information Engineering National Dong Hwa University Hualien Taiwan ROC

In this paper, we present a new data hiding scheme (1,7,4) for grayscale images, where 7 is the number of pixels in each block of the image, 4 is the number of secret bits which can be hidden in each block with restriction that at most one pixel is changed, and the gray value is changed at most 3 from the original one. As shown in the paper, this reaches the theoretical limit MSDR1 of hidden bits in each 7-block of images. A hiding scheme (2,14,8) is obtained as a direct consequence, and one application of this scheme is given to solve the problem of searching in hidden texts in stego-images. To solve this problem, finite automata technique with fuzzy approach is introduced.

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Notice of Removal: The mixed H2/H∞ controller design based on an exterior-point approach

Notice of Removal: The mixed H2/H∞ controller design based ...

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SICE Annual Conference

作者： Yuki Imanishi Yasushi Kami Eitaku Nobuyama Department of Applied Mathematics and Physics Graduate School of Informatics Kyoto University Kyoto Japan Department of Electrical and Computer Engineering National Institute of Technology Hyogo Japan Department of Systems Design and Informatics Kyushu Institute of Technology Fukuoka Japan

This paper is concerned with the mixed H 2 /H ∞ control problem. In general, multi-objective control problems are difficult to be solved theoretically. This is because they are not convex programming problems. In this paper, we propose an exterior-point approach for obtaining a feasible solution of the mixed H 2 /H ∞ control, which produces a controller sequence starting from an infeasible region to a feasible one. One feature of our algorithm is to be able to use any stabilizing controllers as an initial point. A numerical example is given to show the efficiency of our algorithm.

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