VHDL-AMS based genetic optimisation of fuzzy logic controllers

Purpose – This paper presents a VHDL-AMS based genetic optimisation methodology for fuzzy logic controllers (FLCs) used in complex automotive systems and modelled in mixed physical domains. A case study applying this novel method to an active suspension system has been investigated to obtain a new type of fuzzy logic membership function with irregular shapes optimised for best performance. Design/methodology/approach – The geometrical shapes of the fuzzy logic membership functions are irregular and optimised using a genetic algorithm (GA). In this optimisation technique, VHDL-AMS is used not only for the modelling and simulation of the FLC and its underlying active suspension system but also for the implementation of a parallel GA directly in the system testbench. Findings – Simulation results show that the proposed FLC has superior performance in all test cases to that of existing FLCs that use regular-shape, triangular or trapezoidal membership functions. Research limitations – The test of the FLC has only been done in the simulation stage, no physical prototype has been made. Originality/value – This paper proposes a novel way of improving the FLC’s performance and a new application area for VHDL-AMS

VHDL-AMS based genetic optimization of a fuzzy logic controller for automotive active suspension systems

This paper presents a new type of fuzzy logic controller (FLC) membership functions for automotive active suspension systems. The shapes of the membership functions are irregular and optimized using a genetic algorithm (GA). In this optimization technique, VHDL-AMS is used not only for the modeling and simulation of the fuzzy logic controller and its underlying active suspension system but also for the implementation of a parallel GA. Simulation results show that the proposed FLC has superior performance to that of existing FLCs that use triangular or trapezoidal membership functions

VHDL-AMS modeling of an automotive vibration isolation seating system

This paper presents VHDL-AMS model of an automotive vibration isolation seating system with an active electromechanical actuator. Five control algorithms for the actuator are implemented and their efficiencies are investigated by subjecting the system to a number of stimuli, such as a single jolt or noisy harmonic excitations. Simulations were carried out using the SystemVision simulator and results are shown to compare the relative performance merits of the control methods

SystemC-A modeling of an automotive seating vibration isolation system

A modeling methodology for mixed physical domains system in a new modelling Language is presented. The system is automotive seating vibration isolation system with electronic control. It is described and simulated in SystemCA, an extended version of SystemC which provides analogue, mixed-signal and mixed-domain modeling capabilities. Results show that SystemC-A provides efficient means to model and investigate performance of complex mixed-domain systems for automotive applications

A Fast, Numerical Circuit-Level Model of Carbon Nanotube Transistor

Recently proposed circuit-level models of carbon nanotube transistor (CNT) for SPICE-like simulators suffer from numerical complexities as they rely on numerical evaluation of integrals or internal Newton-Raphson iterations to find solutions of non-linear dependencies or both. Recently an approach has been proposed which eliminates the need for numerical integration when calculating the charge densities in CNTFET through the use of piece-wise linear approximation. This paper builds on the effective employment of linear approximation to accelerate the CNT model speed when evaluating the source-drain current of the CNT, but rather than using symbolic solutions as reported, we propose to employ a numerical linearization of charge density dependence on the self-consistent voltage to obtain a dramatic reduction in the CPU time. Our results show a speed up of up to almost four orders of magnitude compared with the theoretical CNT model implemented in FETToy, used as a reference for verifying newer models. Comparisons of drain-source current characteristics of the new model against that in FETToy are presented, confirming the accuracy of the proposed approach

Multi-layer graphene FET compact circuit-level model with temperature effects

This paper presents a circuit-level model of a dual-gate bilayer and four layer graphene field effect transistor (GFET). The model provides an accurate estimation of the conductance at the charge neutrality point (CNP). At the CNP the device has its maximum resistance, at which the model is validated against experimental data of the device off-current for a range of electric fields perpendicular to the channel. The model shows a good agreement for validations carried out at constant and varying temperatures. Using the general Schottky equation, the model estimates the amount of bandgap opening created by the application of an electric field. Also the model shows good agreement when validated against experiment for the channel output conductance against varying gate voltage for both a bilayer and four layer graphene channel

HSPICE implementation of a numerically efficient model of CNT transistor

This paper presents the algorithms of an implementation of a numerically efficient carbon nanotube transistor (CNT) model in HSPICE. The model is derived from cubic spline non-linear approximation of the non-equilibrium mobile charge density. The spline algorithm exploits a rapid and accurate solution of the numerical relationship between the charge density and the self-consistent voltage, which results in the acceleration of deriving the current through the channel without losing much accuracy. The output I-V characteristics of the proposed model have been compared with those of a recent HSPICE implementation of the Stanford CNT model and published experimental I-V curves. The results show superior accuracy of the proposed model while maintaining similar CPU time performance. Two versions of the HSPICE macromodel implementation have been developed and validated, one to reflect ballistic transport only and another with non-ballistic effects. To further validate the model a complementary logic inverter has also been implemented using the proposed technique and simulated in HSPICE

Accurate supercapacitor modeling for energy-harvesting wireless sensor nodes

Supercapacitors are often used in energy-harvesting wireless sensor nodes (EH-WSNs) to store harvested energy. Until now, research into the use of supercapacitors in EH-WSNs has considered them to be ideal or over-simplified, with non-ideal behavior attributed to substantial leakage currents. In this brief, we show that observations previously attributed to leakage are predominantly due to redistribution of charge inside the supercapacitor. We confirm this hypothesis through the development of a circuit-based model which accurately represents non-ideal behavior. The model correlates well with practical validations representing the operation of an EH-WSN, and allows behavior to be simulated over long periods

An Integrated Approach to Energy Harvester Modeling and Performance Optimization

This paper proposes an integrated approach to energy harvester (EH) modeling and performance optimization where the complete mixed physical-domain EH (micro generator, voltage booster, storage element and load) can be modeled and optimized. We show that electrical equivalent models of the micro generator are inadequate for accurate prediction of the voltage booster’s performance. Through the use of hardware description language (HDL) we demonstrate that modeling the micro generator with analytical equations in the mechanical and magnetic domains provide an accurate model which has been validated in practice. Another key feature of the integrated approach is that it facilitates the incorporation of performance enhanced optimization, which as will be demonstrated is necessary due to the mechanicalelectrical interactions of an EH. A case study of a state-of-the-art vibration-based electromagnetic EH has been presented. We show that performance optimization can increase the energy harvesting rate by about 40%