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Evolutionary fuzzy models for nonlinear identification

Evolutionary fuzzy models for nonlinear identification

引用

International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Jérôme Mendes Samuel Pinto Rui Araújo Francisco Souza Institute of Systems and Robotics (ISR-UC) and Department of Electrical and Computer Engineering (DEEC-UC) University of Coimbra Coimbra Portugal

This paper proposes a new method for identification problems for industrial applications based on a Takagi-Sugeno (T-S) fuzzy model. The learning of the T-S model is performed from input/output data to approximate unknown nonlinear processes by a coevolationary genetic algorithm (GA). The proposed method is an automatic tool since it does not require any prior knowledge concerning the structure (e.g. the number of rules) and the database (e.g. antecedent fuzzy sets) of the T-S fuzzy model, and concerning the selection of the adequate input variables and their respective time delays. The proposed methodology is able to design all the parts of the T-S fuzzy prediction model and it is composed by five hierarchical levels. To validate and demonstrate the performance and effectiveness of the proposed algorithm, it is applied on Box-Jenkins benchmark problem.

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Binocular tracking and accommodation controlled by retinal motion flow

Binocular tracking and accommodation controlled by retinal m...

引用

International Conference on Pattern Recognition

作者： J. Batista P. Peixoto H. Araujo ISR-Institute of Systems and Robotics Department of Electrical Engineering University of Coimbra Coimbra Portugal

ISBN: (纸本)0769507506

Describes a tracking and accommodation system controlled by retinal motion flow. The tracking system decomposes two basic behaviors: smooth-pursuit and vergence. Both behaviors are optical flow based. The eye's accommodation (focusing) is based on a focusing-by-vergence approach combining a flow based vergence process with an off-line pre-calibration of the lens focusing odometry. The focusing and tracking system run in parallel and are both velocity controlled.

关键词： Tracking Motion control Retina Focusing Velocity control Geometry Angular velocity Control systems Equations Lenses

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Design and application of Soft Sensor using Ensemble Methods

Design and application of Soft Sensor using Ensemble Methods

引用

International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Symone Soares Rui Araújo Pedro Sousa Francisco Souza Institute of Systems and Robotics (ISR-UC) and Department of Electrical and Computer Engineering (DEEC-UC) University of Coimbra Coimbra Portugal

Industries are faced with the choice of suitable process control policies to improve costs, quality and raw material consumption. In the paper pulp industry, it is important to estimate quickly the Chemical Oxygen Demand (COD), a parameter that is highly correlated to product quality. Soft Sensors (SSs) have been established as alternative to hardware sensors and laboratory measurements for monitoring and control purposes. However, in real setups it is often difficult to get sufficient data for SS development. This work proposes Ensemble Methods (EMs) as a way to improve the SS performance for small datasets. EMs use a set of models to obtain better prediction. Their success is usually attributed to the diversity. Bootstrap and noise injection are used to produce diverse models. Several combinations of EMs are compared. The SS is successfully applied to estimate COD in a pulp process.

关键词： Noise Training Artificial neural networks Diversity reception Chemicals Paper pulp Predictive models

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Human Detection Combining RGB and Thermal Modalities

Human Detection Combining RGB and Thermal Modalities

引用

Intelligent Reality (ICIR), IEEE International Conference on

作者： Chaymaa Fakrane Kennedy O. S. Mota Cristiano Premebida Rui P. Rocha Dept. of Electrical and Computer Engineering (DEEC) Institute of Systems and Robotics (ISR) University of Coimbra Portugal

ISBN: (数字)9798331534424

ISBN: (纸本)9798331534431

This paper addresses a late-fusion approach that combines RGB and thermal (long-wave IR) modalities to enhance human detection in indoor environments for robotic perception domains. The study explores multimodal human detection using YOLO series (v5s-6s and v8s-11s models), demonstrating significant improvements in detection accuracy under challenging lighting conditions on a dataset collected by a mobile robot. The use of a Weighted-Mean (WM) as a late-fusion approach demonstrates favorable results over more complex methods such as neural networks or SVM. The WM approach is simple to implement and has a low computational cost. Additionally, it is more interpretable and modular and allows straightforward adjustments to the weights of the YOLO models and thresholds, facilitating adaptation to the target system's specific needs. The experimental results indicate that the implemented late-fusion approach improves the baseline performance in terms of mean average precision.

关键词： YOLO Support vector machines Adaptation models Accuracy Computational modeling Neural networks Lighting Indoor environment Computational efficiency Mobile robots

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Robot navigation using visual information

Robot navigation using visual information

引用

Annual Conference of Industrial Electronics Society

作者： I. Fonseca J. Dias ISR-Institute of Systems and Robotics Electrical Engineering Department University of Coimbra Coimbra Portugal

This paper addresses the problem of performing navigation with a mobile robot using active vision exploring the image sphere properties in a stereo divergent configuration. The navigational process is supported by the control of the robot's steering and forward movements just using visual information as feedback. The steering control solution is based on the difference between signals of visual motion flow computed in images on different positions of a virtual image sphere. The majority of solutions based on motion flow and proposed until now, were usually very unstable because they normally compute other parameters from the motion flow. In our case the control is based directly on the difference between motion flow signals on different images. Those multiple images are obtained by small mirrors, that simulate cameras positioned in different positions on the image sphere. Another new version for the spherical sensor is under development. The control algorithm described in this work is based on a discrete-event approach to generate a controlling feedback signal for navigation of an autonomous robot with an active vision system as described.

关键词： Navigation Feedback Motion control Robot vision systems Control systems Mobile robots Robot control Mirrors Computational modeling Cameras

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Stable indirect adaptive predictive fuzzy control for industrial processes

Stable indirect adaptive predictive fuzzy control for indust...

引用

International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Jérôme Mendes Rui Araújo Institute of Systems and Robotics (ISR-UC) and Department of Electrical and Computer Engineering (DEEC-UC) University of Coimbra Coimbra Portugal

The paper proposes a stable indirect adaptive fuzzy predictive control, which is based on a discrete-time Takagi-Sugeno (T-S) fuzzy model and on the Generalized predictive control (GPC) algorithm. The T-S fuzzy model is used to approximate the unknown nonlinear plant, that to provide good accuracy in identification of unknown model parameters, three online adaptive laws are proposed. It is demonstrated that the tracking error remains bounded. The stability of closed-loop control system is studied and proved via the Lyapunov stability theory. To validate the theoretical developments and to demonstrate the performance of the proposed control, the controller is applied on a nonlinear simulated laboratory-scale liquid-level process. The simulation results show that the proposed method has a good performance and disturbance rejection capacity in industrial processes.

关键词： Adaptation models Mathematical model Predictive control Predictive models Nonlinear systems Computational modeling

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Optoelectronic proximity sensor for robotics applications

Optoelectronic proximity sensor for robotics applications

引用

Mediterranean Electrotechnical Conference (MELECON)

作者： L. Marques D. Castro U. Nunes A.T. de Almeida ISR-Institute Cor Systems and Robotics Electrical Engineering Department University of Coimbra Portugal

This paper describes an optoelectronic proximity and orientation sensor. We present the sensor modelling and real and simulated results. The sensor is composed by a light emitter and an array of photodetectors that measure the intensity of reflected light on a surface. In this paper we describe the application of this sensor in object prehension tasks performed by a robotic gripper.

关键词： Optoelectronic and photonic sensors Robot sensing systems Sensor arrays Photodetectors Light emitting diodes Sensor systems Optical sensors Sensor phenomena and characterization Tactile sensors Infrared sensors

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Reducing position errors arising from control-space quantisation on a mobile robot

Reducing position errors arising from control-space quantisa...

引用

IEEE International Symposium on Industrial Electronics (ISIE)

作者： R. Araujo A.T. de Almeida Institute of Systems and Robotics ISR and Electrical Engineering Department University of Coimbra Coimbra Portugal

Quantisation of control space is frequently present on a mobile robot. This often results on position errors due to the finite set of available wheels velocities. In this article, the authors present two algorithms that can be used for minimising these position errors on robot motion. The first algorithm can be used to perform pure rotations (no translation) of the mobile robot. The second algorithm can be used to perform straight-line motions, between the mobile robot current position, and a predefined goal position in its working environment. Results of simulation experiments demonstrating the effectiveness of the algorithm are presented.

关键词： Error correction Quantization Mobile robots Wheels Control systems Orbital robotics Digital control Velocity control Kinematics DC motors

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Variable and time-lag selection using empirical data

Variable and time-lag selection using empirical data

引用

International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Francisco Souza Rui Araújo Institute of Systems and Robotics (ISR-UC) and Department of Electrical and Computer Engineering (DEEC-UC) University of Coimbra Coimbra Portugal

The paper proposes a method to select the best variables and respective time-lags for industrial applications when the objective is the estimation of a target variable using the information content of empirical data. No further information is assumed about the process. The problem of jointly selecting the best variables and the respective time-lags is treated as a variable selection problem. This assumption implies an increase of input dimensionality and multicollinearity into input space. Then, a multidimensional mutual information estimator based on the l-nearest neighbor algorithm is used in a forward search procedure to select the best variables and and respective time-lags. To verify the performance of selected variables and delays, the method was successfully applied in two data sets. A least squares support vector machine was used as the main model for the soft sensor in both cases.

关键词： Input variables Delay Mutual information Correlation Computational modeling Estimation Predictive models

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Co-evolutionary genetic Multilayer Perceptron for feature selection and model design

Co-evolutionary genetic Multilayer Perceptron for feature se...

引用

International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Francisco Souza Tiago Matias Rui Araójo Institute of Systems and Robotics (ISR-UC) and Department of Electrical and Computer Engineering (DEEC-UC) University of Coimbra Coimbra Portugal

This paper proposes a method for Soft Sensors design using a Multilayer Perceptron model based on co-evolutionary genetic algorithms, called CEV-MLP. This method jointly and automatically selects the best input variables and the best configuration of the network for the prediction setting. The CEV-MLP is constituted by three levels, the first level selects the best input variables and respective delays set, the second level is composed by the parameters of hidden layers to be optimized (number of neurons in the hidden layers and transfer function), and the third level is the combination of first and second level. The method was successfully applied, and compared with two state-of-the-art methods, in three real datasets. In all the experiments, the proposed method shows the best approximation accuracy, while all the design of the prediction setting is performed automatically.

关键词： Input variables Biological cells Neurons Delay Genetic algorithms Sensors Training

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