Survey of Intelligent Control Techniques for Humanoid Robots

This paper focusses on the application of intelligent control techniques (neural networks, fuzzy logic and genetic algorithms) and their hybrid forms (neuro-fuzzy networks, neuro-genetic and fuzzy-genetic algorithms) in the area of humanoid robotic systems. It represents an attempt to cover the basic principles and concepts of intelligent control in humanoid robotics, with an outline of a number of recent algorithms used in advanced control of humanoid robots. Overall, this survey covers a broad selection of examples that will serve to demonstrate the advantages and disadvantages of the application of intelligent control techniques.     

Simulation of Fuzzy-Logic-Based Intelligent Wheelchair Control System

Fuzzy logic control system for an intelligent wheelchair aimed for assistance by the severely handicapped persons is presented in the paper. It is based on a computer simulation of wheelchair navigation, in which fuzzy logic enables control priority to smoothly alternate between manual and automatic control of the wheelchair in the vicinity of obstacles. The main purpose of designing and simulating this control approach is to improve the safety of a wheelchair in the presence of obstacles. To analyze the success of the wheelchair control, a dynamic model of the wheelchair, together with the models of distance sensors, has been developed using Lagrange analysis.     

Multipurpose modular experimental station for the DiProI beamline of Fermi@Elettra free electron laser

We present a compact modular apparatus with a flexible design that will be operated at the DiProI beamline of the Fermi@Elettra free electron laser (FEL) for performing static and time-resolved coherent diffraction imaging experiments, taking advantage of the full coherence and variable polarization of the short seeded FEL pulses. The apparatus has been assembled and the potential of the experimental setup is demonstrated by commissioning tests with coherent synchrotron radiation. This multipurpose experimental station will be open to general users after installation at the Fermi@Elettra free electron laser in 2011.     

Neural network based expert system for induction motor faults detection

Early detection and diagnosis of incipient induction machine faults increases machinery availability, reduces consequential damage, and improves operational efficiency. However, fault detection using analytical methods is not always possible because it requires perfect knowledge of a process model. This paper proposes a neural network based expert system for diagnosing problems with induction motors using vibration analysis. The short-time Fourier transform (STFT) is used to process the quasi-steady vibration signals, and the neural network is trained and tested using the vibration spectra. The efficiency of the developed neural network expert system is evaluated. The results show that a neural network expert system can be developed based on vibration measurements acquired on-line from the machine.     

Influence of Field Effects on the Performance of InGaAs-Based Terahertz Radiation Detectors

A detailed electrical characterization of high-performance bow-tie InGaAs-based terahertz detectors is presented along with simulation results. The local surface potential and tunnelling current were scanned over the surfaces of the detectors by means of Kelvin probe force microscopy (KPFM) and scanning tunnelling microscopy (STM), which also enabled the determination of the Fermi level. Current-voltage curves were measured and modelled using the Synopsys Sentaurus TCAD package to gain deeper insight into the processes involved in detector operation. In addition, we performed finite-difference time-domain (FDTD) simulations to reveal features related to changes in the electric field due to the metal detector contacts. The investigation revealed that field-effect-induced conductivity modulation is a possible mechanism contributing to the high sensitivity of the studied detectors.     

Analyzing probabilistic pushdown automata

The paper gives a summary of the existing results about algorithmic analysis of probabilistic pushdown automata and their subclasses.     

Automated resolution of connector architectures using constraint solving (ARCAS method)

In current software systems, connectors play an important role by encapsulating the communication and coordination logic. Since they share common patterns (elements) depending on characteristics of the connections, the elements can be predefined and reused. A method of connector implementation based on a composition of predefined elements naturally comprises two steps: resolution of the connector architecture, and creation of the actual connector code based on the architecture. However, manual resolution of a connector architecture is very difficult due to the number of factors to be considered. Thus, the challenge is to come up with an automated method, able to address all the important factors. In this paper, we present a method for automated resolution of connector architectures based on constraint solving techniques. We exploit a propositional logic with relational calculus for defining a connector theory, a constraint specification reflecting both the predefined parts and the important resolution factors, and employ a constraint solver to find a suitable connector architecture as a model of the theory. As a proof of the concept, we show how the theory can be captured in the Alloy language and resolved via the Alloy Analyzer.     

SAHPPA: a novel power pinch analysis approach for the design of off-grid hybrid energy systems

This work proposes a novel approach called stand-alone hybrid system power pinch analysis (SAHPPA), which is particularly applicable for the design of off-grid distributed energy generation systems. The enhanced graphical tool employs new ways of utilising the recently introduced demand composite curve and supply composite curve while honouring and adapting fundamental energy systems engineering concepts. The SAHPPA method is capable of optimising the capacity of both the power generators and energy storage for biomass (i.e. non-intermittent) and solar photovoltaic (i.e. intermittent) energy technologies, which is a contribution to the emerging area of power pinch analysis. In addition, the procedure considers all possible efficiency losses in the overall system encompassing the charging–discharging and current inversion processes.