Chi-Un Lei

IIR Approximation of FIR Filters Via Discrete-Time Vector Fitting

We present a novel technique for approximating finite-impulse-response (FIR) filters with infinite-impulse-response (IIR) structures through extending the vector fitting (VF) algorithm, used extensively for continuous-time frequency-domain rational approximation, to its discrete-time counterpart called VFz. VFz directly computes the candidate filter poles and iteratively relocates them for progressively better approximation. Each VFz iteration consists of the solutions of an overdetermined linear equation and an eigenvalue problem, with real-domain arithmetic to accommodate complex poles. Pole flipping and maximum pole radius constraint guarantee stability and robustness against finite-precision implementation. Comparison against existing algorithms confirms that VFz generally exhibits fast convergence and produces highly accurate IIR approximants.

MFTI: matrix-format tangential interpolation for modeling multi-port systems

Numerous algorithms to macromodel a linear time-invariant (LTI) system from its frequency-domain sampling data have been proposed in recent years [1,2,3,4,5,6,7,8], among which Loewner matrix-based tangential interpolation proves to be especially suitable for modeling massive-port systems [6, 7,8]. However, the existing Loewner matrix-based method follows vector-format tangential interpolation (VFTI), which fails to explore all the information contained in the frequency samples. In this paper, a novel matrix-format tangential interpolation (MFTI) is proposed, which requires much fewer samples to recover the system and yields better accuracy when handling under-sampled, noisy and/or ill-conditioned data. A recursive version of MFTI is proposed to further reduce the computational complexity. Numerical examples then confirm the superiority of MFTI over VFTI.

GHM: a generalized Hamiltonian method for passivity test of impedance/admittance descriptor systems

A generalized Hamiltonian method (GHM) is proposed for passivity test of descriptor systems (DSs) which describe impedance or admittance input-output responses. GHM can test passivity of DSs with any system index without minimal realization. This frequency-independent method can avoid the time-consuming system decomposition as required in many existing DS passivity test approaches. Furthermore, GHM can test systems with singular D + DT where traditional Hamiltonian method fails, and enjoys a more accurate passivity violation identification compared to frequency sweeping techniques. Numerical results have verified the effectiveness of GHM. The proposed method constitutes a versatile tool to speed up passivity check and enforcement of DSs and subsequently ensures globally stable simulations of electrical circuits and components.

Global optimization of common subexpressions for multiplierless synthesis of multiple constant multiplications

In the context of multiple constant multiplication (MCM) design, we propose a novel common subexpression elimination (CSE) algorithm that models the optimal synthesis of coefficients into a 0-1 mixed-integer linear programming (MILP) problem. A time delay constraint is included for synthesis. We also propose coefficient decompositions that combine all minimal signed digit (MSD) representations and the shifted sum (difference) of coefficients. In the examples we demonstrate, the proposed solution space further reduces the number of adders/subtractors in the MCM synthesis.

Design of hybrid continuous-time discrete-time delta-sigma modulators

Recent attention has been drawn to the hybrid Delta-Sigma (DeltaSigma) structure featuring the integration of continuous-time (CT) and discrete-time (DT) structures in the loop filter. It combines the accurate loop filter characteristic of a DT DeltaSigma modulator and the inherent anti-aliasing of a CT DeltaSigma modulator. We present a design methodology for building a CT-DT DeltaSigma modulator via the transformation from a DT DeltaSigma modulator prototype. We also demonstrate the tradeoff of applying this structure to cascaded Delta-Sigma modulators compared to pure CT or DT implementations.

Efficient Linear Macromodeling via Discrete-Time Time-Domain Vector Fitting

We present a discrete-time time-domain vector fitting algorithm, called TD-VFz, for rational function macromodeling of port-to-port responses with discrete time-sampled data. The core routine involves a two-step pole refinement process based on a linear least-squares solve and an eigenvalue problem. Applications in the macromodeling of practical circuits demonstrate that TD-VFz exhibits fast computation, excellent accuracy, and robustness against noisy data. We also utilize an quasi-error bound unique to the discrete-time setting to facilitate the determination of approximant model order.

A hybrid MPPT method for Photovoltaic systems via estimation and revision method

Maximum Power Point Tracking (MPPT) methods can be classified into direct and indirect approaches. They are used to improve the efficiency of power conversion in Photovoltaic (PV) systems. However, a review of present literature implies that the indirect methods never produce accurate results. Meanwhile, the conventional direct Perturb and Observe (P&O) method has two problems: oscillations at steady state and slow dynamic response under changing environment conditions. Estimation and Revision (ER) method is proposed in this paper to overcome these limitations by the alternative use of MPP estimation and MPP revision process. The efficiency of the ER method is verified in an MPPT system implemented with a specific DC-DC converter and an adopted PV module.

IIR Approximation of FIR Filters Via Discrete-Time Hybrid-Domain Vector Fitting

We present a discrete-time hybrid-domain vector fitting algorithm, called HD-VFz, for the IIR approximation of FIR filters with an arbitrary combination of time-and frequency-sampled responses. The core routine involves a two-step pole refinement process based on a linear least-squares solve and an eigenvalue problem. Through hybrid-domain data approximation and digital partial fraction basis with relative stability consideration, HD-VFz exhibits fast computation and remarkable fitting accuracy in both time and frequency domains.

Low-cost global MPPT scheme for Photovoltaic systems under partially shaded conditions

Maximum Power Point Tracking (MPPT) is a technique applied to improve the efficiency of power conversion in Photovoltaic (PV) systems. Under partially shadowed conditions, the Power-Voltage (P-V) characteristic exhibits multiple peaks and the existing MPPT methods such as the Perturb and Observe (P&O) are incapable of searching for the Global Maximum Power Point (GMPP). This paper proposes a low-cost on-line MPPT scheme to overcome this drawback. By using hybrid numerical searching process, the operating point approaches Local Maximum Power Points (LMPPs) gradually and the GMPP is caught by comparing all the LMPPs. Simulation results prove the effectiveness and correctness of the proposed method.

Building an Intelligent Laboratory Environment via a Cyber-Physical System

Activities in laboratories, workshops, and offices can be significantly affected by their ambiance and environmental conditions, such as lighting, humidity, and temperature. This research focuses on laboratories and aims to improve peoples performance of activities inside them. To this end, we have developed a cyber-physical system (CPS) for a smart/intelligent laboratory environment which is able to dynamically and automatically interpret and regulate environmental conditions. In this paper, we present the CPS development framework. The proposed CPS can measure, analyze, and regulate the thermal comfort. In order to prolong the lifetime of the system, mechanisms for low-volume communication, distributed computation, and habit-based adaptive control are proposed. Evaluations of an on-site deployment verify the functionality of the proposed CPS. Although our focus is on laboratories, this research can be applied to other similar environments, which are intended to support human performance and productivity, and has implications for the creation of smart cities.