Adaptive high-performance velocity evaluation based on a high resolution time-to-digital converter

In this paper, an improved method is presented to derive the velocity information in a pulse-number measurement/time-duration-type digital tachometer by processing its pulse train. The method incorporates encoder pulse counting and very accurate time measurement. The velocity sampling interval is not constant but is continuously modified. An adaptive algorithm provides a wide-range velocity evaluation with very good accuracy. The adaptation of the next sampling period, according to the instant velocity, results in better response times at low speeds and a very high accuracy at medium and high speeds. Compared to currently known methods, the time measurement resolution and, consequently, the velocity accuracy is improved by using the proposed method due to the inclusion of high-resolution time-to-digital converters in the design. The proposed configuration can be implemented in specific hardware by using field-programmable gate arrays (FPGAs), thus saving the computational power of the digital signal processor that supervises the system for higher level control tasks

An intelligent based decision support system for the detection of meat spoilage

In food industry, safety and quality are considered important issues worldwide that are directly related to health and social progress. Meat spoilage is the result of decomposition and the formation of metabolites, caused by the growth and enzymatic activity of microorganisms, and it presents not only a health hazard but an economic burden to the producer. In this research work, we explore the potential of Fourier transform infrared (FTIR) spectroscopy in combination of principal components analysis and neuro-fuzzy modelling, to determine beef spoilage microorganisms during aerobic storage at chill and abuse temperatures. FTIR spectra were obtained from the surface of beef samples, while culture microbiological analysis determined the total viable count (TVC) for each sample. The dual purpose of the proposed modelling approach is not only to classify beef samples in the respective quality class (i.e., fresh, semi-fresh and spoiled), but also to predict their associated microbiological population directly from FTIR spectra. The proposed neuro-fuzzy network model utilises a prototype defuzzification scheme, whereas the number of input membership functions is directly associated to the number of rules, reducing thus, the “curse of dimensionality” problem. Results confirmed the superiority of the adopted methodology compared to other schemes such as multilayer perceptron and the partial least squares techniques and indicated that FTIR spectral information in combination with an efficient choice of a learning-based modelling scheme could be considered as an alternative methodology for the accurate evaluation of meat spoilage

Terrain-based navigation for underwater vehicles using an ultrasonic scanning system

In this paper an approach to the field of outdoor robotic navigation with a focus on underwater simultaneous localization and mapping (SLAM) is proposed that utilizes ultrasonic scanning images. Experimental results from the implementation of a SLAM algorithm with real data are presented. The projected landmark detection process constructs a map of the environment and generates navigation estimates based on an adaptive delayed nearest-neighbor algorithm. The feature extraction and validation processes are resolved at the sensor level using a simple local maximum-level detection algorithm on the range data. This paper presents experimental results from our research efforts in the above area, using data from water tank trials and a remotely operated vehicle operating in a shallow water environment

Variable structure TITO fuzzy-logic controller implementation for a solar air-conditioning system

The design and implementation of a Two-Input/Two-Output (TITO) variable structure fuzzy-logic controller for a solar-powered air-conditioning system is described in this paper. Two DC motors are used to drive the generator pump and the feed pump of the solar air-conditioner. The first affects the temperature in the generator of the solar air-conditioner, while the second, the pressure in the power loop. The difficulty of Multi-Input/Multi-Output (MIMO) systems control is how to overcome the coupling effects among each degree of freedom. First, a traditional fuzzy-controller has been designed, its output being one of the components of the control signal for each DC motor driver. Secondly, according to the characteristics of the system’s dynamics coupling, an appropriate coupling fuzzy-controller (CFC) is incorporated into a traditional fuzzy-controller (TFC) to compensate for the dynamic coupling among each degree of freedom. This control strategy simplifies the implementation problem of fuzzy control, but can also improve the control performance. This mixed fuzzy controller (MFC) can effectively improve the coupling effects of the systems, and this control strategy is easy to design and implement. Experimental results from the implemented system are presented

A new method for digital encoder adaptive velocity/acceleration evaluation using a TDC with picosecond accuracy

In this paper, a new methodology for deriving the velocity and the acceleration information of a digital encoder through processing its pulse train, is presented. The proposed method is based on accurate time measurement (with picosecond accuracy) as well as encoder pulse counting in adaptively changing time intervals, providing thus a wide-range velocity evaluation with very good accuracy. The method offers better response times at low speeds and very high-accuracy at the full range of measured velocities. By using the proposed method, the velocity measurement accuracy is improved compared to currently known methods, since high-resolution time-to-digital converters (TDC) are included in the design. The increased accuracy in velocity measurement allows the application of the simple arithmetic differentiation method on the velocity information in order to derive the acceleration, which in other cases would not be suggested due to accumulated quantization noise. A digital signal processor (DSP) also allows the implementation of numerous other methods to calculate acceleration. The proposed configuration has been implemented in specific hardware (FPGA), reserving thus the computational power of the system controlling DSP for high-level control tasks