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A fast digital fuzzy logic controller: FPGA design and implementation

A fast digital fuzzy logic controller: FPGA design and imple...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： K.M. Deliparaschos F.I. Nenedakis S.G. Tzafestas Intelligent Robotics and Automation Laboratory Department of Electrical Engineering and Computer Science National and Technical University of Athens Athens Greece

This paper describes an improved approach to design a Takagi-Sugeno zero-order type fast parameterized digital fuzzy logic controller (DFLC) processing only the active rules (rules that give a non-null contribution for a given input data set), at high frequency of operation, without significant increase in hardware complexity. To achieve this goal, an improved method of designing the fuzzy controller model is proposed that significantly reduces the time required to process the active rules and effectively increases the input data processing rate. The DFLC discussed in this paper achieves an internal core processing speed of at least 200 MHz, featuring two 8-bit inputs and one 12-bit output, with up to seven trapezoidal shape membership functions per input and a rule base of up to 49 rules. The proposed architecture was implemented in a field programmable gate array (FPGA) chip with the use of a very high-speed integrated-circuits hardware-description-language (VHDL) and advanced synthesis and place and route tools

关键词： Fuzzy logic Digital control Field programmable gate arrays Takagi-Sugeno model Process control Frequency Hardware Design methodology Fuzzy control Data processing

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Recognizing interaction from a robot's perspective

Recognizing interaction from a robot's perspective

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： T. Salter F. Michaud K. Dautenhahn D. Letourneau S. Caron LABORIUS-Research Laboratory on Mobile Robotics and Intelligent Systems Department of Electrical Engineering and Computer Engineering Université de Sherbrook Sherbrooke QUE Canada Adaptive Systems Research Group School of Computer Science University of Herfordshire Hatfield UK

For meaningful interaction between a robot and a human, an autonomous robot must recognize whether the experienced situation is created by people or by the environment. Using only proprioceptive data from a mobile robotic platform, we discover that it is possible to distinguish sensory data patterns involving interaction. These patterns are obtained whilst navigating varying environments, both human populated and unpopulated. The paper reports the initial set of trials using Roball, a spherical mobile robot. Also described is the experimental methodology currently followed to validate the hypothesis that child interaction can be perceived directly from navigation sensors onboard a robotic platform.

关键词： Robot sensing systems Mobile robots Human robot interaction Navigation intelligent robots Sensor phenomena and characterization Infrared sensors Educational institutions Plastics Mobile computing

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Wall following and obstacle avoidance results from a multi-DSP sonar ring on a mobile robot

Wall following and obstacle avoidance results from a multi-D...

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IEEE International Conference on Mechatronics and Automation

作者： S. Fazli L. Kleeman ARC Centre for Perceptive and Intelligent Machines in Complex Environments Intelligent Robotics Research Centre Department of Electrical and Computer Systems Engineering Monash University VIC Australia

Sensing capabilities of a multi-DSP sonar ring are demonstrated with wall following and obstacle avoidance behaviour. The autonomous mobile robot called "Sombrero" moves perpendicular to the nearest object on the left while controlling the distance to that object and generates high quality sonar maps. The wall following and obstacle avoidance behaviour is very simple due to the accurate and timely range and bearing (incidence angle) information provided by the advanced sonar ring. The advanced sonar ring consists of 48 ultrasonic transducers, 24 acting as transceivers and 24 acting as receivers, seven custom designed DSP echo processor boards and six analogue boards. The sonar ring is able to cover 360 degrees around robot with simultaneously firing of all 24 transmitters. Transmission and echo analysis are performed at repetition rates of about 10 Hz, for ranges up to six metres. Accurate distance and bearing measurements of objects are performed by the DSP system using matched filtering techniques. The robot is able to follow walls of various shapes such as a square, circle, concave corner and convex corner. Sombrero controls its motion based on the range and bearing data captured from the advanced sonar ring every 100 msec while moving with a constant speed. Experimental results illustrate the effectiveness of the sonar ring and the quality of the generated local maps.

关键词： Mobile robots Digital signal processing Sonar measurements Ultrasonic transducers Transceivers Process design Transmitters Performance analysis Performance evaluation Matched filters

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Transference of evolved unmanned aerial vehicle controllers to a wheeled mobile robot

Transference of evolved unmanned aerial vehicle controllers ...

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2005 IEEE International Conference on robotics and Automation

作者： Barlow, Gregory J. Mattos, Leonardo S. Grant, Edward Oh, Choong K. Center for Robotics and Intelligent Machines Department of Electrical and Computer Engineering North Carolina State University Raleigh NC 27695 U.S. Naval Research Laboratory 4555 Overlook Ave. S.W. Washington DC 20375 Robotics Institute Carnegie Mellon University 5000 Forbes Avenue Pittsburgh PA 15213

ISBN: (纸本)078038914X

Transference of controllers evolved in simulation to real vehicles is an important issue in evolutionary robotics (ER). We have previously evolved autonomous navigation controllers for fixed wing UAV applications using multi-objective genetic programming (GP). Controllers were evolved to locate a radar source, navigate the UAV to the source efficiently using on-board sensor measurements, and circle around the emitter. We successfully tested an evolved UAV controller on a wheeled mobile robot. A passive sonar system on the robot was used in place of the radar sensor, and a speaker emitting a tone was used as the target in place of a radar. Using the evolved navigation controller, the mobile robot moved to the speaker and circled around it. The results from this experiment demonstrate that our evolved controllers are capable of transference to real vehicles. Future research will include testing the best evolved controllers by using them to fly real UAVs. ©2005 IEEE.

关键词： Unmanned vehicles

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Ranked centroid projection: a data visualization approach for self-organizing maps

Ranked centroid projection: a data visualization approach fo...

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International Joint Conference on Neural Networks (IJCNN)

作者： G.G. Yen Zheng Wu Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK USA

The self-organizing map (SOM) is an efficient tool for visualizing high-dimensional data as it performs a topology-presenting projection of the input space on a low-dimensional grid. To utilize the information provided by the SOM and obtain an approximation of the data structure, a separate data projection method is usually needed. However, most of the SOM projection methods are computationally expensive when the size of the data set becomes large. In this paper, we present an intuitive and effective SOM projection method with comparatively low computational complexity for the purpose of cluster visualization. This method maps data vectors on the output space based on their responses to different prototype vectors. High-resolution maps can be obtained with a relatively small network size. The proposed method is demonstrated using both an artificial and a real world data set.

关键词： Data visualization Self organizing feature maps Prototypes Neurons Data structures Computational complexity intelligent systems intelligent control Control systems Laboratories

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Fault classification on vibration data with wavelet based feature selection scheme

Fault classification on vibration data with wavelet based fe...

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Annual Conference of Industrial Electronics Society

作者： G.G. Yen W.F. Leong Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK USA

Fault classification based upon vibration data is an essential building block of a sophisticated conditional based monitoring (CBM) system. Multiple sensor channels are called for to assure the redundancy and to achieve the desired reliability and accuracy. The shortcoming of using multiple sensor input channels is the need to deal with high dimensional features set, a computational expensive task in classification. It is vital to reduce the feature dimension via an effective feature extraction and feature selection scheme. A simple wavelet based feature selection scheme is proposed. This scheme overcomes the disadvantages faced by existing feature selection methods, by producing a general feature set, reducing the dimensionality of features and requiring no prior information of the problem domain. The proposed feature selection scheme is based on the strategy of "divide and conquer" that significantly reduce the computation time without compromising the classification performance. The simulation results show the proposed feature selection scheme provides at least 65% reduction of the total number of features without compromising the classification performance.

关键词： Vibrations Condition monitoring Redundancy Feature extraction Linear discriminant analysis Principal component analysis intelligent sensors Reliability engineering Sensor systems Multidimensional systems

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Distributed mining of partial periodic patterns in sequences

Distributed mining of partial periodic patterns in sequences

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作者： Hsiao, Han-Wen Tsai, Meng-Shu Tsai, Jeffrey J. P. Department of Computer Science and Information Engineering Asia University Taiwan Taiwan Institute of Information Technology Asia University Taiwan Taiwan Department of Computer Science University of Illinois Chicago United States Taichung Healthcare and Management University Department of Computer Science and Information Engineering Department of Biotechnology and Bioinformatics Department of Electrical Engineering and Computer Science University of Illinois Chicago Distributed Real-Time Intelligent Systems Laboratory

It has been an important task of discovering frequent fragments as particular patterns from large sequence databases generated from a variety of applications. In general, the patterns to be discovered may partially and asynchronously exist in sequences, and even contain gaps. In addition, it is necessary to collect the information regarding the locations and frequencies of the patterns. How to enumerate candidate patterns for evaluation without exponentially increasing the computation is another problem. In this paper, the modified periodicity transform is proposed to meet the requirements mentioned above. Also, a distributed computing framework is implemented to perform the mining task more efficiently. Both synthetic and biological sequences are utilized to examine the approach. The experimental results demonstrate the efficiency and effectiveness the system.

关键词： Data mining

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Comparison of non-uniform optimal quantizer designs for speech coding with adaptive critics and particle swarm

Comparison of non-uniform optimal quantizer designs for spee...

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Conference Record of the IEEE Industry Applications Society Annual Meeting (IAS)

作者： W. Zha G.K. Venayagamoorthy Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla MO USA

This paper presents the design of a companding non-uniform optimal scalar quantizer for speech coding. The quantizer is designed using two neural networks to perform the nonlinear transformation. These neural networks are used in the front and back ends of a uniform quantizer. Two approaches are presented in this paper namely adaptive critic designs (ACD) and particle swarm optimization (PSO), aiming to maximize the signal to noise ratio (SNR). The comparison of these optimal quantizer designs over bit rate range of 3 to 6 is presented. The perceptual quality of the coding is evaluated by the International Telecommunication Union's Perceptual Evaluation of Speech Quality (PESQ) standard.

关键词： Speech coding Particle swarm optimization Quantization Neural networks Bit rate Speech analysis Signal to noise ratio Telecommunication standards Humans Signal resolution

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Neural networks based non-uniform scalar quantizer design with particle swarm optimization

Neural networks based non-uniform scalar quantizer design wi...

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IEEE Swarm Intelligence Symposium, SIS

作者： W. Zha G.K. Venayagamoorthy Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla MO USA

Quantization is a crucial link in the process of digital speech communication. Non-uniform quantizer such as the logarithm quantizers are commonly used in practice. In this paper, a companding non-uniform quantizer is designed using two neural networks to perform the nonlinear transformation. Particle swarm optimization is applied to find the weights of neural networks such that the signal to noise ratio (SNR) is maximized. Simulation results on different speech samples are presented and the proposed quantizer design is compared with the logarithm quantizer for bit rates ranging from 3 to 8.

关键词： Neural networks Particle swarm optimization Quantization Bit rate Signal to noise ratio Humans Ear Nonlinear distortion Speech processing Oral communication

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A neural network based optimal wide area control scheme for a power system

A neural network based optimal wide area control scheme for ...

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Conference Record of the IEEE Industry Applications Society Annual Meeting (IAS)

作者： G.K. Venayagamoorthy S. Ray Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla MO USA

With deregulation of the power industry, many tie lines between control areas are driven to operate near their maximum capacity, especially those serving heavy load centers. Wide area control systems (WACSs) using wide-area or global signals can provide remote auxiliary control signals to local controllers such as automatic voltage regulators, power system stabilizers, etc to damp out inter-area oscillations. This paper presents the design and the DSP implementation of a nonlinear optimal wide area controller based on adaptive critic designs and neural networks for a power system on the real-time digital simulator (RTDS/spl reg/). The performance of the WACS as a power system stability agent is studied using the Kundur's two area power system example. The WACS provides better damping of power system oscillations under small and large disturbances even with the inclusion of local power system stabilizers.

关键词： Neural networks Optimal control Control systems Power system control Power systems Power system simulation Power system stability Automatic voltage control Automatic control Power industry

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