An Adaptive Observer-based Robust Estimator of Multi-sinusoidal Signals

This paper presents an adaptive observer-based robust estimation methodology of the amplitudes, frequencies and phases of biased multi-sinusoidal signals in presence of bounded perturbations on the measurement. The parameters of the sinusoidal components are estimated on-line and the update laws are individually controlled by an excitation-based switching logic enabling the update of a parameter only when the measured signal is sufficiently informative. This way doing, the algorithm is able to tackle the problem of over-parametrization (i.e., when the internal model accounts for a number of sinusoids that is larger than the true spectral content) or temporarily fading sinusoidal components. The stability analysis proves the existence of a tuning parameter set for which the estimator\u2019s dynamics are input-to-state stable with respect to bounded measurement disturbances. The performance of the proposed estimation approach is evaluated and compared with other existing tools by extensive simulation trials and real-time experiments

Signal Recovery From 1-Bit Quantized Noisy Samples via Adaptive Thresholding

In this paper, we consider the problem of signal recovery from 1-bit noisy measurements. We present an efficient method to obtain an estimation of the signal of interest when the measurements are corrupted by white or colored noise. To the best of our knowledge, the proposed framework is the pioneer effort in the area of 1-bit sampling and signal recovery in providing a unified framework to deal with the presence of noise with an arbitrary covariance matrix including that of the colored noise. The proposed method is based on a constrained quadratic program (CQP) formulation utilizing an adaptive quantization thresholding approach, that further enables us to accurately recover the signal of interest from its 1-bit noisy measurements. In addition, due to the adaptive nature of the proposed method, it can recover both fixed and time-varying parameters from their quantized 1-bit samples.Comment: This is a pre-print version of the original conference paper that has been accepted at the 2018 IEEE Asilomar Conference on Signals, Systems, and Computer

Fast Adaptive Robust Differentiator Based Robust-Adaptive Control of Grid-Tied Inverters with a New L Filter Design Method

In this research, a new nonlinear and adaptive state feedback controller with a fast-adaptive robust differentiator is presented for grid-tied inverters. All parameters and external disturbances are taken as uncertain in the design of the proposed controller without the disadvantages of singularity and over-parameterization. A robust differentiator based on the second order sliding mode is also developed with a fast-adaptive structure to be able to consider the time derivative of the virtual control input. Unlike the conventional backstepping, the proposed differentiator overcomes the problem of explosion of complexity. In the closed-loop control system, the three phase source currents and direct current (DC) bus voltage are assumed to be available for feedback. Using the Lyapunov stability theory, it is proven that the overall control system has the global asymptotic stability. In addition, a new simple L filter design method based on the total harmonic distortion approach is also proposed. Simulations and experimental results show that the proposed controller assurances drive the tracking errors to zero with better performance, and it is robust against all uncertainties. Moreover, the proposed L filter design method matches the total harmonic distortion (THD) aim in the design with the experimental result

Improved Transients in Multiple Frequencies Estimation via Dynamic Regressor Extension and Mixing

A problem of performance enhancement for multiple frequencies estimation is studied. First, we consider a basic gradient-based estimation approach with global exponential convergence. Next, we apply dynamic regressor extension and mixing technique to improve transient performance of the basic approach and ensure non-strict monotonicity of estimation errors. Simulation results illustrate benefits of the proposed solution.Comment: This paper is submitted for the ALCOSP 2016 conferenc

Passivity-based harmonic control through series/parallel damping of an H-bridge rectifier

Nowadays the H-bridge is one of the preferred solutions to connect DC loads or distributed sources to the single-phase grid. The control aims are: sinusoidal grid current with unity power factor and optimal DC voltage regulation capability. These objectives should be satisfied, regardless the conditions of the grid, the DC load/source and the converter nonlinearities. In this paper a passivity-based approach is thoroughly investigated proposing a damping-based solution for the error dynamics. Practical experiments with a real converter validate the analysis.

Self-Commissioning Algorithm for Inverter Non-Linearity Compensation in Sensorless Induction Motor Drives

In many sensorless field-oriented control schemes for induction motor (IM) drives, flux is estimated by means of measured motor currents and control reference voltages. In most cases, flux estimation is based on the integral of back-electromotive-force (EMF) voltages. Inverter nonlinear errors (dead-time and on-state voltage drops) introduce a distortion in the estimated voltage that reduces the accuracy of the flux estimation, particularly at low speed. In the literature, most of the compensation techniques of such errors require the offline identification of the inverter model and offline postprocessing. This paper presents a simple and accurate method for the identification of inverter parameters at the drive startup. The method is integrated into the control code of the IM drive, and it is based on the information contained in the feedback signal of the flux observer. The procedure applies, more in general, to all those sensorless ac drives where the flux is estimated using the back-EMF integration, not only for IM drives but also for permanent-magnet synchronous motor drives (surface-mounted permanent magnet and interior permanent magnet). A self-commissioning algorithm is presented and tested for the sensorless control of an IM drive, implemented on a fixed-point DSP. The feasibility and effectiveness of the method are demonstrated by experimental result