Analog Circuits Research Articles

Extreme multistability of fractional-order hyperchaotic system based on dual memristors and its implementation

In this paper, a fractional-order hyperchaotic system based on dual memristors is proposed by introducing flux-controlled and charge-controlled memristors into a simple RLC circuit. Dynamics of the hyperchaotic system are investigated using bifurcation diagrams, Lyapunov exponents spectrum (LEs), phase diagrams, time-domain diagrams, spectral entropy (SE) and C0 complexity. The results show that it has a plane of equilibria and exhibits rich dynamical characteristics, including hyperchaos, homogeneous and heterogeneous extreme multistability. Meanwhile, the transient transition phenomena as well as the effect of parameters on the complexity and chaotic behavior of the system are also studied. Furthermore, the practical implementation of the system is realized through analog and digital circuit. The experimental results validate the correctness of the theoretical analysis and help to make better use of the hyperchaotic system in applications such as secure communications.

Fault detection in analog electronic circuits using fuzzy inference systems and particle swarm optimization

Fault detection in analog circuits is of great importance to predict the correct operation of the circuit. For this purpose, soft computing techniques such as those based on the application of fuzzy inference systems stand out. However, given the large variability that can exist in analog circuits due to component tolerance, the initial fuzzy inference system (FIS) may not be able to accurately diagnose the different hard faults. This study presents a methodology to diagnose and detect the faults that can occur in analog circuits, which is based on the development of a FIS, starting from a specific fault situation in the analog circuit, and subsequently on the optimization of the membership functions using an evolutionary algorithm so that the adjusted FIS can classify and predict different failure situations. To this end, the application of optimization techniques based on particle swarm optimization (PSO) will be analyzed to develop a FIS capable of predicting different faults. In addition, pattern search algorithm will also be analyzed. A Sallen-Key band-pass filter and a single stage of a small-signal amplifier are used as test circuits. The proposed methodology shows that it is possible to accurately predict the faults that could arise in the circuits under study.

Fully real-time configurable analogue implementation of continuous-time transfer function: Application on fractional controller

This paper proposes a new electronic analog circuit to realize real-time fully configurable continuous-time transfer function. The proposed circuit serves various purposes, including smart controllers, fractional-order controllers, optimal controllers, anti-aliasing filter, and programmable filters. The input signal of the transfer function is continuous and remains continuous throughout the circuit until the output signal is obtained. The proposed approach decomposes the transfer function into elementary first and/or second-order low-pass filters. A new analog first-order low-pass filter circuit is presented, offering advantages over conventional active first-order low-pass filters circuits. These benefits include DC gain and time constant independent of resistor ohmic values, enabling the use of smaller resistors and capacitors for low frequencies, and an expanded frequency working range. Similarly, a new analog circuit for a second-order low-pass filter is proposed, specifically used to obtain complex conjugate poles. The use of digital potentiometers and digital switches controlled by a micro-controller, makes this analog circuit configurable in real-time. As an application, the new circuit is used to realize fractional integrator controller. The circuit gives good similarity between theoretical and experimental measurements.

Investigation of an efficient high cooling-capacity Stirling-type pulse tube refrigerator with passive rod displacer operating at 173 K

Pulse tube refrigerator (PTR) with passive rod displacer is of great potential to realize high-efficiency refrigeration and can be a feasible substitute for the vapor compression system in ultra-low temperature cold storage. However, PTRs with passive rod displacer in that application require high efficiency and substantial cooling capacity, which still need to be developed in previous research. In this paper, a high cooling-capacity PTR with passive rod displacer operating at 173 K was designed, fabricated, and investigated. The special property of acoustic power recovery was exhibited based on an electrical circuit analogy model and energy flow analysis. The structural parameters of PTR with passive rod displacer were optimized by one-dimensional numerical software. The experimental results showed that a cooling capacity of 157.5 W at 173 K was obtained with an input electric power of 500 W. The corresponding relative Carnot efficiency reached 21.8 %. The phase difference between the displacer and piston decreased slightly from 58.1° with the increase of cooling temperature when charging pressure and operating frequency were 2.8 MPa and 65 Hz, respectively. The phase difference was determined by the operating frequency and was slightly affected by charging pressure, cooling temperature, and input electric power. Based on the validated numerical models, PTR with passive rod displacer and inertance-tube-type PTR were compared. The numerical results showed that both enthalpy and PV power enlarged at the T-junction in the PTR with passive rod displacer due to acoustic power recovery. According to the acoustic-mechanical–electrical coupling phasor diagram, the phase difference between pressure and piston displacement decreased because of the mass flow superposition at the T-junction, affecting the output capability of the linear compressor. The efficient high cooling-capacity prototype verifies that PTR with passive rod displacer has a bright future in ultra-low temperature engineering applications.

Design and Comparison of Constant Transconductance Architectures

Constant transconductance (Gm) biasing circuits, as the name suggests, generate a bias current that ensures that the Gm of a MOS transistor remains constant. The Gm of a MOS transistor is a very important parameter as various other parameters of a circuit such as the gain, UGB (Unity Gain Bandwidth, poles, and zeros are strongly dependent upon it. Every analog circuit in a chip is subjected to varying PVT (Process, Voltage, and Temperature) conditions. This leads to a varying Gm of the devices, and hence the parameters such as the gain and UGB also tend to vary. Hence, constant Gm biasing is crucial in systems, where the parameters are expected to be constant regardless of the external factors. The majority of constant Gm biasing circuits make use of an external off-chip resistor. While this is a reasonable solution, it adds to the cost, area, and complexity of the solution. Hence, it is vital to model and design all the required functionalities within the chip, eliminating the requirement for any external components. In this paper, different architectures of constant Gm biasing circuits are designed and simulated in Cadence Virtuoso software. The proposed architecture has an error of 6.42% in the variation of transconductance, which is a significant improvement concerning the other architectures simulated. Additionally, the proposed architecture does not require any off-chip components while the other architectures require an off-chip resistor. Hence, the proposed solution has reduced cost and complexity.

Circuit analogy unveiled the haemodynamic effects of the posterior cross vein in the wing vein networks.

We investigated the wing vein network topology in fruit flies and observed that the posterior cross vein (PCV) disrupts the symmetry of the entire network. The fluidic engineering function of this vein's disposition remains unexplored although the wing vein network is known to transport blood. We examined the fluid mechanical effects of the PCV's disposition on this blood-transporting network through numerical simulations involving the removal and rearrangement of the vein, avoiding impractical physical manipulation. We characterised the geometry of each wing membrane cell, a portion of the wing membrane surrounded by a group of veins, by determining the ratio of its surface area to the contact area with the veins. We considered this ratio in association with the flow velocities of seeping water from the blood within the veins to the membrane and evaporating water from the membrane, based on the mass conservation law. We observed that the division of a membrane cell by the PCV maximises the ratio of the areas in the divided cell on the wing-tip side by virtually shifting this vein's connections in our geometric membrane model. We derived blood flow rate and pressure loss within the venous network from their geometry, using an analogy of the venous network with a circuit consisting of hydraulic resistors based on Kirchhoff and Ohm's laws. The overall pressure loss in the network decreased by 20% with the presence of the PCV functioning as a paralleled hydraulic resistor. By contrast, any other cross-vein computationally arranged on another membrane cell as the PCV's substitution did not exhibit a larger reduction in the pressure loss. Overall, our numerical analyses, leveraging geometry and a circuit analogy, highlighted the effects of the PCV's presence and position on the blood-transporting vein network.

A Compact Model for Carbon Nanotube Field Effect Transistors Incorporating Temperature Effects and Application for Operational Amplifier Design

Semiconducting carbon nanotubes (CNTs), characterized by high carrier mobility and atomic thickness, are considered ideal channel materials for building high-performance and ultimate-scale field-effect transistors for future electronics. Here, we present a data-calibrated compact model of CNT field-effect transistors (CNTFETs) that incorporates temperature effects using the virtual source approach. The proposed model also includes the self-heating effect. Temperature effect was characterized by the influence of temperature on devices, achieved through establishing a temperature-dependent semi-empirical model of carrier mobility and carrier velocity. The proposed model can be easily implemented in a simulator. We designed a two-stage operational amplifier (OPAMP) using the proposed model at 32 nm technology. Compared with other studies, the designed CNTFET-based OPAMP demonstrates lower power consumption, which is beneficial for exploring the biological applications of low-power analog circuits in portable electronic devices. Furthermore, the impact of thermal variations on the design of OPAMP, as per the proposed model, was delineated. Investigations revealed that our circuit maintains a high common mode rejection ratio, which diminishes as the temperature increases and exhibits a moderate gain value that escalates with temperature.

Wireless wavelength measurement system with temperature compensation using filter-free wavelength sensors

Abstract Portable wavelength detection systems have been developed for various environmental and biochemical applications. Conventional systems have some limitations as they are unable to adapt to changes in wavelength and rely on optical filters or slits to distinguish between different wavelengths. To address these limitations, a filter-free wavelength sensor system was proposed, utilizing the absorption coefficient of silicon to identify wavelengths. The proposed system comprises an analog circuit for measuring photocurrent from a filter-free wavelength sensor, integrated with a temperature sensor and microcontroller for signal processing. The proposed system can measure currents with a resolution of 1.2 pA within a 30 nA range, achieving a coefficient of determination of 0.999 for measured currents in relation to light intensity. The microcontroller features a temperature compensation algorithm, enabling wireless control and data transmission. Applying temperature compensation reduced the rate of errors in the data by 61%. By eliminating the need for optical components, a wireless measurement system was developed that can accurately identify wavelengths.

In‐panel ambient light eliminating differential circuit applied to active pixel fingerprint sensor

AbstractIn this paper, we present a novel approach to counter the influence of ambient light on photodetectors used in applications like biometric recognition and environmental sensing. The proposed solution introduces a circuit‐based technique that utilizes signal differencing to subtract ambient light signals before they reach the integrated circuit (IC). The process involves row and column differential signals, akin to analog circuit differential amplifiers. Simulations validate the circuit's functionality, showing its effectiveness in reducing ambient light impact. However, image reconstruction after differencing introduces blurriness due to the accumulation of noise. An alternative bidirectional fusion method is suggested, resulting in a clearer representation of features without noise accumulation. This innovative approach promises to enhance photodetector performance in challenging lighting conditions for various applications.

A fractional-order hyperchaotic system that is period in integer-order case and its application in a novel high-quality color image encryption algorithm

A new fractional-order 5D hyperchaotic system based on memristor is constructed in this paper, with the speciality that the system exists chaotic and hyperchaotic states in the fractional-order case, while in periodic state in the integer-order. In addition, it has a variety of special phenomena at fractional-order such as infinite initial value range, parameter-dependent offset-boosting and amplitude control, attractor coexistence, and fractional order complexity greater than integer order. The correctness and feasibility of the system is verified by analog circuit simulation and hardware circuit implementation. Combining this system with image encryption algorithms, two new scrambling algorithms and a diffusion algorithm are proposed. And a high-quality encryption scheme that can be applied to a wide range of color images is proposed. The scheme is found to have excellent security after verification by various security analyses and comparison with other literatures. This paper provides a basis for the superiority of fractional-order chaotic systems and provides new methods in the field of image encryption.

A synthetic position decoding technology for rotary transformers based rotor position measurement system.

This article proposes a rotary transformer position decoding scheme for motor drive control. In this scheme, a simple analog circuit is used to design the excitation circuit and signal conditioning circuit. Demodulate the modulated sine/cosine signal through software and decode it through a phase locked loop (PLL) to obtain the implemented position signal. This scheme completely avoids the use of traditional, specialized decoding chips. At the same time, in order to make the position decoding scheme applicable to different motor drive control platforms, a single-cycle partition average based pulse signal estimation method is proposed for converting the angle position into pulse signals similar to the output of an encoder's phases A, B, and Z, which are referred to as A/B/Z signals in the paper. In order to experimentally validate the proposed scheme, a software decoding platform based on the STM32F407 was built and compared with the decoding results of the chip. The effectiveness and accuracy of the proposed scheme were verified, and it can be effectively applied in the field of motor drive control.

Biphasic action potentials in an individual cellular neural network cell

Hardware circuit that can effectively simulate biological neurons is an important basis for neuromorphic computation. Cellular neural network (CNN) cell is the basic information processor of a CNN, which acts like a neuron in the brain and has good circuit realizability. An individual memristive CNN cell is constructed by using a memristor instead of a linear resistor for imitating the ion channel time-varying conductance, in which abundant biphasic chaotic and periodic spiking activities are uncovered. This provides a new way to simulate biological neurons at the level of analog circuits. This paper first deduces the mathematical model of the memristive CNN cell, analyzes the equilibrium stability and then explores its dynamical behaviors based on numerical simulation. The results display that the different spiking activities can be effectively regulated by the system parameters and excitation parameters. Furthermore, the analog circuit of the memristive CNN cell is designed and the PSpice-based circuit simulations are performed to verify the correctness of the numerical simulations.

Effect of Filters in Photoplethysmography Analog Signals Using Open-Source LTspice Software

Analog signal processing plays a crucial role in the realm of biomedical signal analysis. This study investigates the application of analog signal processing techniques in the domain of biomedical signals, focusing on enhancing the quality and reliability of recorded physiological data. The primary emphasis is on the implementation of analog filters and amplifiers to address challenges such as noise reduction, signal conditioning, and overall signal improvement. The processing of physiological signals, such as photoplethysmography (PPG), necessitates the use of amplifiers and filters within a range of 0.4 to 5Hz. Signal noise can stem from various sources, including the test subject’s muscle movement, respiration, humming, power line interference, or even from the device itself. The research methodology involves a comparison of 3 different order of Butterworth filter circuits and their impact on the signal. The test input signal is derived from an SpO$_2$ simulator, read by a standard PPG sensor, and processed by the internal 12-bit ADC of Nucleo-F429ZI. The resulting data is stored in CSV format for subsequent use in filter design simulations with SPICE. For analog circuit designers, the utilization of SPICE in the form of LTspice proves invaluable. This open software, LTspice, boasts a simple yet powerful interface, facilitating a focus on the conceptualization and performance of the design

Theoretical Impedance Calculation Method for Air‐Core Coils

Coils are designed to have impedance characteristics appropriate for any use of the sensors, analog circuits and so on. The impedance characteristics of a coil depends on the coil shape and used materials, and these factors make coil design difficult. Therefore, we proposed a convenient method to obtain the impedance characteristics of a coil by theoretical calculation of the inductance, resistance, and capacitance. The difference between the calculated and measured values was within 15%, which demonstrated the usefulness of the proposed method. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Analytical studies on third-order chaotic systems with Sprott type nonlinearities and their microcontroller implementation

The evolution of chaos in a generic third-order autonomous mathematical model with nonlinearities described by simple mathematical functions is reported in this paper. The nonlinearities termed as Sprott type nonlinear functions are used in the design of a class of third-order systems exhibiting chaotic behavior. The evolution and confirmation of chaos in their system dynamics is observed through numerical simulation studies of one-parameter bifurcation diagrams and Lyapunov exponents. Analytical solutions are developed for systems with piecewise-linear nonlinear functions. Finally, the microcontroller implementation of the third-order system equations with different nonlinearities and analog circuit simulation results are presented to confirm the numerical and analytical results. Chaos in generic third-order systems studied through numerical, analytical and microcontroller results has been reported in the literature for the first time.

2D BDiode – A switchable bidirectional diode for analog electronic circuits fabricated entirely from 2D materials

The advent of two-dimensional (2D) materials has led to innovative and compact electronic devices with remarkable properties. In this work, we introduce a switchable bidirectional diode (2D BDiode), fabricated entirely using different 2D materials, that serves as a fundamental building block for various analog circuit applications. This proof-of-concept diode exhibits the ability to control the flow of current in both forward and reverse bias configurations, enabling advanced functionality in the realm of analog circuit design. We provide a SPICE-based model for the diode based on current-voltage device characterization, capturing its behavior under different biasing conditions, and finally demonstrate a few potential use cases of the 2D BDiode including AC/DC conversion, DC/AC conversion and charge pump circuits.

Post-layout simulation driven analog circuit sizing

Post-layout simulation driven analog circuit sizing

A Method of Diagnosing Analog Circuit Soft Faults Using Boruta Features and LightGBM

Modern electronic power systems rely heavily on analog circuits. The accurate detection of analog circuit faults, especially soft faults, is of great significance for the maintenance and inspection of electronic systems. This paper proposes the application of the Boruta feature selection method to the field of the soft fault diagnosis of analog circuits to screen out low-dimensional and efficient feature components from the high-dimensional time-domain statistical features and frequency-domain features of circuit responses. Then, the feature components are used as the input to train the LightGBM classification model, and the Bayesian optimization method is introduced to optimize the model’s hyperparameters. Finally, the trained fault diagnosis model is verified in two typical experimental circuits, and satisfactory accuracy is obtained.

A Nonlinear Megastable System with Diamond-Shaped Oscillators

Benefiting from trigonometric and hyperbolic functions, a nonlinear megastable chaotic system is reported in this paper. Its nonlinear equations without linear terms make the system dynamics much more complex. Its coexisting attractors’ shape is diamond-like; thus, this system is said to have diamond-shaped oscillators. State space and time series plots show the existence of coexisting chaotic attractors. The autonomous version of this system was studied previously. Inspired by the former work and applying a forcing term to this system, its dynamics are studied. All forcing term parameters’ impacts are investigated alongside the initial condition-dependent behaviors to confirm the system’s megastability. The dynamical analysis utilizes one-dimensional and two-dimensional bifurcation diagrams, Lyapunov exponents, Kaplan–Yorke dimension, and attraction basin. Because of this system’s megastability, the one-dimensional bifurcation diagrams and Kaplan–Yorke dimension are plotted with three distinct initial conditions. Its analog circuit is simulated in the OrCAD environment to confirm the numerical simulations’ correctness.

Artificial intelligence in analogue circuit design

Analog circuit design plays an integral part in modern society; however, traditional approaches often fall short in terms of efficiency and effectiveness. This paper explores the application and challenges presented by artificial intelligence (AI) technologies in analog circuit design. The objective of this paper was to evaluate the capacity of artificial intelligence technologies such as machine learning, deep learning and reinforcement learning to advance circuit modeling, optimization and layout design processes. A comprehensive literature review and analysis were performed. The study finds that while AI can make significant contributions to circuit design, several challenges must first be overcome. These include data scarcity for training AI models and the opaque nature of AI decisions which prevent their widespread acceptance. Finally, future research directions such as creating synthetic data or developing more interpretable AI models were identified as potential future research avenues.