Quantized passive filtering for switched delayed neural networks

The issue of quantized passive filtering for switched delayed neural networks with noise interference is studied in this paper. Both arbitrary and semi-Markov switching rules are taken into account. By choosing Lyapunov functionals and applying several inequality techniques, sufficient conditions are proposed to ensure the filter error system to be not only exponentially stable, but also exponentially passive from the noise interference to the output error. The gain matrix for the proposed quantized passive filter is able to be determined through the feasible solution of linear matrix inequalities, which are computationally tractable with the help of some popular convex optimization tools. Finally, two numerical examples are given to illustrate the usefulness of the quantized passive filter design methods

Input-to-State Stability for Dynamical Neural Networks with Time-Varying Delays

A class of dynamical neural network models with time-varying delays is considered. By employing the Lyapunov-Krasovskii functional method and linear matrix inequalities (LMIs) technique, some new sufficient conditions ensuring the input-to-state stability (ISS) property of the nonlinear network systems are obtained. Finally, numerical examples are provided to illustrate the efficiency of the derived results

Advances in Solid State Circuit Technologies

This book brings together contributions from experts in the fields to describe the current status of important topics in solid-state circuit technologies. It consists of 20 chapters which are grouped under the following categories: general information, circuits and devices, materials, and characterization techniques. These chapters have been written by renowned experts in the respective fields making this book valuable to the integrated circuits and materials science communities. It is intended for a diverse readership including electrical engineers and material scientists in the industry and academic institutions. Readers will be able to familiarize themselves with the latest technologies in the various fields

Development and modelling of a versatile active micro-electrode array for high density in-vivo and in-vitro neural signal investigation

The electrophysiological observation of neurological cells has allowed much knowledge to be gathered regarding how living organisms are believed to acquire and process sensation. Although much has been learned about neurons in isolation, there is much more to be discovered in how these neurons communicate within large networks. The challenges of measuring neurological networks at the scale, density and chronic level of non invasiveness required to observe neurological processing and decision making are manifold, however methods have been suggested that have allowed small scale networks to be observed using arrays of micro-fabricated electrodes. These arrays transduce ionic perturbations local to the cell membrane in the extracellular fluid into small electrical signals within the metal that may be measured. A device was designed for optimal electrical matching to the electrode interface and maximal signal preservation of the received extracellular neural signals. Design parameters were developed from electrophysiological computer simulations and experimentally obtained empirical models of the electrode-electrolyte interface. From this information, a novel interface based signal filtering method was developed that enabled high density amplifier interface circuitry to be realised. A novel prototype monolithic active electrode was developed using CMOS microfabrication technology. The device uses the top metallization of a selected process to form the electrode substrate and compact amplification circuitry fabricated directly beneath the electrode to amplify and separate the neural signal from the baseline offsets and noise of the electrode interface. The signal is then buffered for high speed sampling and switched signal routing. Prototype 16 and 256 active electrode array with custom support circuitry is presented at the layout stage for a 20 μm diameter 100 μm pitch electrode array. Each device consumes 26.4 μW of power and contributes 4.509 μV (rms) of noise to the received signal over a controlled bandwidth of 10 Hz - 5 kHz. The research has provided a fundamental insight into the challenges of high density neural network observation, both in the passive and the active manner. The thesis concludes that power consumption is the fundamental limiting factor of high density integrated MEA circuitry; low power dissipation being crucial for the existence of the surface adhered cells under measurement. With transistor sizing, noise and signal slewing each being inversely proportional to the dc supply current and the large power requirements of desirable ancillary circuitry such as analogue-to-digital converters, a situation of compromise is approached that must be carefully considered for specific application design

Robust finite-time fault estimation for stochastic nonlinear systems with Brownian motions

Motivated by real-time monitoring and fault diagnosis for complex systems, the presented paper aims to develop effective fault estimation techniques for stochastic nonlinear systems subject to partially decoupled unknown input disturbances and Brownian motions. The challenge of the research is how to ensure the robustness of the proposed fault estimation techniques against stochastic Brownian perturbations and additive process disturbances, and provide a rigorous mathematical proof of the finite-time input-to-stabilization of the estimation error dynamics. In this paper, stochastic input-to-state stability and finite-time stochastic input-to-state stability of stochastic nonlinear systems are firstly investigated based on Lyapunov theory, leading to simple and straightforward criteria. By integrating augmented system approach, unknown input observer technique, and finite-time stochastic input-to-state stability theory, a highly-novel fault estimation technique is proposed. The convergence of the estimation error with respect to un-decoupled unknown inputs and Brownian perturbations is proven by using the derived stochastic input-to-state stability and finite-time stochastic input-to-state stability theorems. Based on linear matrix inequality technique, the robust observer gains can be obtained in order to achieve both stability and robustness of the error dynamic. Finally, the effectiveness of the proposed fault estimation techniques is demonstrated by the detailed simulation studies using a robotic system and a numerical example

Perturbation Observer based Adaptive Passive Control and Applications for VSC-HVDC Systems and FACTS Devices

The technology of voltage source converter based high voltage direct current (VSC-HVDC) system and devices used in flexible AC transmission systems (FACTS) has evolved significantly over the past two decades. It is used to effectively enhance power system stability. One of the important issues is how to design an applicable nonlinear adaptive controller for these devices to effectively handle the system nonlinearities and uncertainties. Passive control (PC) has been proposed for the control of nonlinear systems based on Lyapunov theory, which has the potential to improve the system damping as the beneficial system nonlinearities are remained instead of being fully cancelled. However, PC is not applicable in practice as it requires an accurate system model. Adaptive passive control (APC) and robust passive control (RPC) have been developed to handle some specific type of system uncertainties based on strict assumptions on system structure and uncertainty. However, their applications are limited as various system uncertainties exist. This thesis aims to develop a perturbation observer based adaptive passive control (POAPC) to make PC applicable in practice. The combinatorial effect of system nonlinearities, parameter uncertainties, unmodelled dynamics and time-varying external disturbances is aggregated into a perturbation, which is estimated by a perturbation observer (PO). The proposed approach does not require an accurate system model and can handle various system uncertainties. POAPC is applied to two-terminal VSC-HVDC systems to handle various system uncertainties. The VSC-HVDC system model is firstly developed, the proposed controller can inject an extra system damping and only the measurement of direct current (DC) voltage, active and reactive power is needed. The effectiveness ofPOAPC is verified by simulation in comparison with that of passive control (PC) and proportional-integral (PI) control. Moreover, a hardware experiment is carried out to verify its implementation feasibility and applicability. A passive controller is designed for multi-terminal VSC-HVDC (VSC-MTDC) systems via energy shaping, in which the dynamics related to the active power, reactive power, and DC cable voltage is transformed into an output strictly passive form. Then the remained internal dynamics related to DC cable current and common DC voltage is proved to be asymptotically stable in the context of Lyapunov criterion. PC is applied on a four-terminal VSC-MTDC system under eight cases to evaluate its control performance. POAPC is developed on the VSC-MTDC system to maintain a consistent control performance under different operating points and provide a significant robustness to parameter uncertainties, together with other unmodelled dynamics and time-varying external disturbances. Simulation results are provided to evaluate the control performance of POAPC in comparison to that of PI control and PC. Perturbation observer based coordinated adaptive passive control (POCAPC) is proposed for excitation controller (EC) and FACTS controller on both single machine infinite bus (SMIB) systems and multi-machine power systems. Only the range of control Lyapunov function (CLF) is needed and the dependence of an accurate system model can be partially reduced, thus POCAPC can be easily applied to multi-machine power systems. Its control performance is compared with that of conventional proportional-integral-derivative and lead-lag (PID+LL) control, coordinated passive control (CPC) and coordinated adaptive passive control (CAPC) on both an SMIB system and a three-machine power system by simulation. Then a hardware-in-the-loop (HIL) test is undertaken to verify the implementation feasibility of the proposed controller

Analog Computing using 1T1R Crossbar Arrays

Memristor is a novel passive electronic device and a promising candidate for new generation non-volatile memory and analog computing. Analog computing based on memristors has been explored in this study. Due to the lack of commercial electrical testing instruments for those emerging devices and crossbar arrays, we have designed and built testing circuits to implement analog and parallel computing operations. With the setup developed in this study, we have successfully demonstrated image processing functions utilizing large memristor crossbar arrays. We further designed and experimentally demonstrated the first memristor based field programmable analog array (FPAA), which was successfully configured for audio equalizer and frequency classifier demonstration as exemplary applications of such memristive FPAA (memFPAA)

DESIGN OF SMART SENSORS FOR DETECTION OF PHYSICAL QUANTITIES

Microsystems and integrated smart sensors represent a flourishing business thanks to the manifold benefits of these devices with respect to their respective macroscopic counterparts. Miniaturization to micrometric scale is a turning point to obtain high sensitive and reliable devices with enhanced spatial and temporal resolution. Power consumption compatible with battery operated systems, and reduced cost per device are also pivotal for their success. All these characteristics make investigation on this filed very active nowadays. This thesis work is focused on two main themes: (i) design and development of a single chip smart flow-meter; (ii) design and development of readout interfaces for capacitive micro-electro-mechanical-systems (MEMS) based on capacitance to pulse width modulation conversion. High sensitivity integrated smart sensors for detecting very small flow rates of both gases and liquids aiming to fulfil emerging demands for this kind of devices in the industrial to environmental and medical applications. On the other hand, the prototyping of such sensor is a multidisciplinary activity involving the study of thermal and fluid dynamic phenomenon that have to be considered to obtain a correct design. Design, assisted by finite elements CAD tools, and fabrication of the sensing structures using features of a standard CMOS process is discussed in the first chapter. The packaging of fluidic sensors issue is also illustrated as it has a great importance on the overall sensor performances. The package is charged to allow optimal interaction between fluids and the sensors and protecting the latter from the external environment. As miniaturized structures allows a great spatial resolution, it is extremely challenging to fabricate low cost packages for multiple flow rate measurements on the same chip. As a final point, a compact anemometer prototype, usable for wireless sensor network nodes, is described. The design of the full custom circuitry for signal extraction and conditioning is coped in the second chapter, where insights into the design methods are given for analog basic building blocks such as amplifiers, transconductors, filters, multipliers, current drivers. A big effort has been put to find reusable design guidelines and trade-offs applicable to different design cases. This kind of rational design enabled the implementation of complex and flexible functionalities making the interface circuits able to interact both with on chip sensors and external sensors. In the third chapter, the chip floor-plan designed in the STMicroelectronics BCD6s process of the entire smart flow sensor formed by the sensing structures and the readout electronics is presented. Some preliminary tests are also covered here. Finally design and implementation of very low power interfaces for typical MEMS capacitive sensors (accelerometers, gyroscopes, pressure sensors, angular displacement and chemical species sensors) is discussed. Very original circuital topologies, based on chopper modulation technique, will be illustrated. A prototype, designed within a joint research activity is presented. Measured performances spurred the investigation of new techniques to enhance precision and accuracy capabilities of the interface. A brief introduction to the design of active pixel sensors interface for hybrid CMOS imagers is sketched in the appendix as a preliminary study done during an internship in the CNM-IMB institute of Barcelona