Distributed Secondary Voltage Control for DC Microgrids with Consideration of Asynchronous Sampling

This paper studies the distributed secondary control of DC microgrids (MGs) in the case of asynchronous sampling, including both the stability condition and accurate consensus algorithm. The asynchrony means that the update actions of each distributed generation (DG) based on the local information and information received from neighbors are independent of the actions of others at sampled discrete times, which would cause deviation from the accurate convergence and even lead to instability in the worst case. First, a small-signal model of MG installed with secondary voltage control is established to include the individual sampling periods. A stability criterion based on the periodic continuity of sampling instant offset is thus formulated to reveal a stability mapping of multiple sampling. By quantifying the accuracy deviations caused by the asynchrony, an improved ratio consensus strategy is proposed that allows the deviation to be estimated accurately via an auxiliary signal and compensated with respect to the eventual equilibrium to produce an exact solution. Our approach customizes the stability and accuracy for distributed secondary control considering asynchronous sampling in MG, which has been ignored in most existing literature. The effectiveness of the proposed methodology is verified by simulations.

Synchronization of Transmission Systems with ANS-DM Codecs

Adaptive Delta Modulation with Non-uniform Sampling (ANS-DM) is one of the waveform coding techniques, where a sampling instant and a quantization step size are adapted to the signal. The ANS-DM modulator produces an output binary stream, that carries information about the signal and includes necessary data of coder parameters (sampling instant and quantization step). In the demodulator, these values are recovered for proper signal reconstruction. The paper reports the problem of synchronizing clocks (transmitting and receiving) in the (ANS-DM) delta codecs systems. The original synchronization method, valuable in systems dedicated to the transmission of the bits with variable time duration was projected and experimentally verified. Performed measurements and observations have shown the elimination of the synchronization loss phenomenon.

Model Predictive Current Control with Asymmetric Stacked Multilevel Inverter and LCL-Filter Based STATCOM

The work presented in this paper deals with a proposal of a new topology of a multilevel inverter to act as a Static synchronous Compensator (STATCOM). The proposed inverter is the five-level Asymmetric Stacked Multi-Level Inverter (ASMLI). One of the essential features of this inverter that distinguishes it from the conventional types is that it achieves the required voltage levels with fewer switching devices, leading to simplifying the control process. Moreover, the work includes using a Finite Control Set Model Predictive Current Control (FCS-MPCC) to control the proposed structure. The FCS-MPCC control strategy performs the finite optimization process at the current sampling instant to provide the optimum switching states to the inverter at the next sampling instant. Therefore, this control strategy allows injecting harmonic current and reactive power compensation to reduce source current distortion and improve the voltage profile and power factor. The optimization mechanism reduces the cost function, which is a function of measuring the network current's deviation from the reference value and how the capacitor voltage deviates from the required values. LCL-filter was used to connect this setup to the grid, and its resonance was actively damped using the multivariable capabilities of the FCS-MPCC. The proposed control framework was simulated using MATLAB/Simulink 9.1 environment and tested in a distorted and healthy network compared to a conventional two-level converter with RL-filter. The STATCOM was used to inject reactive power to raise the source power factor to unity and reduce source current harmonics by injecting harmonic current. The proposed prototype could absorb 70% of source current harmonics, which is nearly 25% better than a conventional inverter, inject an appropriate amount of reactive power, and raise the source power factor to unity in two case scenarios. The performance achieved was promising at steady-state operation and speedy response during transients with balanced capacitors voltages.

Multiple-Vector Model Predictive Control with Fuzzy Logic for PMSM Electric Drive Systems

This article presents a multiple-vector finite-control-set model predictive control (MV-FCS-MPC) scheme with fuzzy logic for permanent-magnet synchronous motors (PMSMs) used in electric drive systems. The proposed technique is based on discrete space vector modulation (DSVM). The converter’s real voltage vectors are utilized along with new virtual voltage vectors to form switching sequences for each sampling period in order to improve the steady-state performance. Furthermore, to obtain the reference voltage vector (VV) directly from the reference current and to reduce the calculation load of the proposed MV-FCS-MPC technique, a deadbeat function (DB) is added. Subsequently, the best real or virtual voltage vector to be applied in the next sampling instant is selected based on a certain cost function. Moreover, a fuzzy logic controller is employed in the outer loop for controlling the speed of the rotor. Accordingly, the dynamic response of the speed is improved and the difficulty of the proportional-integral (PI) controller tuning is avoided. The response of the suggested technique is verified by simulation results and compared with that of the conventional FCS-MPC.

A fast-moving horizon estimation method based on the symplectic pseudospectral algorithm

In this paper, a fast-moving horizon state estimation algorithm for nonlinear continuous systems with measurement noises and model disturbances is developed. The optimization problem required to be solved at each sampling instant is formulated into a backward nonlinear optimal control problem over the finite past. Once prior knowledge of the observed system is available, constraints can be further imposed. The highly efficient and accurate symplectic pseudospectral algorithm is taken as the core solver, which leads to the symplectic pseudospectral moving horizon estimation (SP-MHE) method. The developed SP-MHE is first evaluated by numerical simulations for a hovercraft. Then the developed method is extended to parameter estimation and applied to a chaotic system with an unknown parameter. Simulation results show that the SP-MHE can generate accurate estimations even under large sampling periods or large noise where regular filters fail. In addition, the SP-MHE exhibits excellent online efficiency, suggesting it can be used for scenarios where the sampling period is relatively small.

Aperiodic sampled-data control of distributed networked control systems with time-delay

This paper proposes a hybrid aperiodic sampled-data mechanism for the control of interconnected subsystems with time-delay. The proposed aperiodic sampled-data mechanism comprises of two stages. In the first stage, the next sampling instant for each subsystem is computed using self-triggering strategy. Thereafter, in the second stage, an event-triggering condition is checked at these sampling instants for each subsystem and signal is transmitted to the controller only if the event-triggering condition is violated. Further, to reduce the computational complexity involved in the proposed triggering mechanism, another triggering mechanism with integrated event-triggering and self-triggering is developed. Also, an upper bound on delay for each subsystem is computed to ensure the stability of distributed networked control system. The results proposed are validated using a simulation example. A comparison of the proposed technique with other triggering mechanisms in terms of sampling instants, number of transmissions to the controller, maximum delay bound and other performance measures is drawn through simulation example.

FAST ADAPTIVE GENERALIZED PREDICTIVE CONTROL FOR SYSTEMS WITH VARIABLE PARAMETERS

This paper proposes a fast predictive control structure with online model update according to process parametric variations. The proposed controller is based on the Generalized Predictive Control (GPC) algorithm, but it integrates the recursive least squares identification method with a variable forgetting factor to estimate at each iteration the parameters of a linear structure model used for multi-step ahead prediction. For a system with constraints on the process variables, the resulting optimization problem of GPC is solved using quadratic programming based on the Alternate Direction Method of Multipliers, which allows the control signal to be obtained with small computational effort. In order to validate the proposed algorithm an experimental case study that considers the speed control of a direct current motor and the proposed controller embedded in a microcontroller STM32F303K8T6 is presented. Experimental results use as baseline the GPC with fixed model parameters and show that the proposed fast adaptive predictive control structure is able to keep almost the same transient response for all the considered operating points of the motor, while GPC presents high oscillations at operating conditions far from the one used to obtain the nominal model. Even though the proposed controller needs to solve two optimization problems at each sampling instant, it can run about 60 times in a second in the microcontroller used in this study

Finite Control Set Model Predictive Control for Parallel Connected Online UPS System under Unbalanced and Nonlinear Loads

In this paper, the finite control set model predictive control (FCS–MPC) technique-based controller is proposed for the inverter of the uninterrupted power supply (UPS) system. The proposed controller uses the mathematical model of the system to forecast the response of voltage for each possible switching state for every sampling instant. Following this, the cost function was used to determine the switching state, applied to the next sampling instant. First, the proposed control strategy was implemented for the single inverter of the UPS system. Finally, the droop control strategy was implemented for parallel inverters to guarantee actual power sharing among a multiple-parallel UPS system. To validate the performance of the proposed controller under steady-state conditions and dynamic-transient conditions, extensive simulations were conducted using MATLAB/Simulink. The proposed work shows a low computational burden, good steady state performance, fast transient response, and robust results against parameter disturbances as compared to linear control. The simulation results showed that total harmonic distortion (THD) for the linear load was 0.9% and THD for the nonlinear load was 1.42%.