International Journal of Industrial Electronics, Control and Optimization
Volume:2 Issue: 1, winter 2019

This paper investigates the stabilization problem of an autonomous Linear Time Invariant (LTI) switched system with interval uncertainty and unstable subsystems. It is proved that the system would be stable by using a common Lyapanov function whose derivative is negative and bounded by a quadratic function within activation regions of each subsystem. First, a sufficient condition for the stability of an Linear Time Invariant switched system with interval uncertainty, based on the convex analysis and interval set theoretical approach, is resented and proved. Moreover, conservatism in the stability robustness bound is obtained. Then, a switching control law is designed to shift the Linear Time Invariant switched system among subsystems to ensure the decrease of the Lyapanov function within the state space. Finally, in order to decrease the switching frequency and to avoid chattering, the switching law is modified. Two examples are included to demonstrate the effectiveness of the theoretical findings.

Limitation of fossil fuel reserves and environmental pollution resulting from their use, especially in cities, as well as low efficiency of current energy converters lead to the tendency towards the use of more efficient energy converters and renewable energy sources. The use of distributed generation (DG) is one of the appropriate solutions in this regard. There are various techniques provided to control these converters. In this study a new technique of Direct Power Control (DPC) is proposed to connect distributed generation sources to the nationwide grid. This technique not only adds power of distributed generation sources to the grid, but also is capable to compensate the reactive and harmonic power of non-linear loads as well. In this study, Converters’ voltage references for generating compensation current are directly calculated in synchronous rotating coordinate system in each period of sampling; then, a proper pulse width modulation (PWM) generates the used voltages. The proposed DPC technique has some advantages including simple algorithm of fast dynamic as well as fixed switching frequency and small sampling frequency. The performance of the proposed direct control technique is confirmed by simulation results

This paper presents a simple and direct power control approach to control a single-phase grid-connected boost inverter (GCBI) for renewable energy applications. A DC voltage source and a single-phase single-stage boost inverter that is connected to the grid by an L filter form the power injection system (PIS). Unlike the conventional voltage source inverters (VSIs), the boost inverter can generate an AC output voltage with amplitude larger than the DC input one, only in a single stage. In comparison with multi-stage power conversion systems, the aforementioned inverter has less number of devices and components which results in low cost and higher efficiency. Nevertheless, the boost inverter suffers from undesirable dynamic behavior and extreme fluctuation response that makes it difficult to control. Thus, the proposed power injection control system consists of two parts. First, a proper state-feedback control scheme is designed to increase damping and also improve the stability of the closed-loop system. Then, the direct power control strategy is employed to control and track the desired powers that should be injected into the grid. Simulation results are presented to validate the effectiveness of the proposed control strategy

A single-phase distributed generation (DG) sources embedded in three-phase microgrids develop with a fast-paced trend, it is important to make use of suitable power sharing trategies among multiple DGs and utilizing the power generation of these units to the full capacity. This paper presents an innovative sliding mode-based power control strategy for microgrids. The multi-bus microgrid consists of three-phase DG units that are two photovoltaic (PV) array, and three single-phase DG units including PV, battery and fuel cell (FC). The dynamic modeling of all DGs is based on voltage source inverter (VSI). One of the three-phase DGs is responsible for frequency and voltage control, and the other one for current ontrol. The single-phase DGs are controlled based on the three-phase DGs. Finally, the voltage and power control operations are implemented in a per-unit system. The proposed control trategy has a fast response and the ability to trace a reference signal with a low steady-state error compared with the PI controller; moreover, it provides the accurate active and reactive power sharing among energy units under various loading and fault conditions along with robustness against the microgrid parameters. Additionally, the ability to maintain the dc-link voltage and frequency constant is another feature of this controller

In this paper, a full-order sliding mode controller, based on adaptive neuro-fuzzy inference system is proposed as approximator, for controlling nonlinear chaotic systems in presence of uncertainty. At first, the full-order sliding mode controller is designed for the system in the absence of uncertainty such that the system states are converged to the sliding surface. Then, adding uncertainty to system equations, convergence of the method is illustrated using simulations. By assuming that a part of the system dynamics is uncertain and only input-output data is partly available, adaptive neuro-fuzzy inference system is used in off-line mode to approximate the uncertain dynamics of the system based on input-output data. The proposed method can effectively solve the problems of the sliding-based methods, such as chattering phenomenon and singularity. The simulation results, applied to the well-known nonlinear systems namely PMSM and plasma torch systems when they behave in chaotic mode, demonstrate effectiveness and fidelity of the proposed control method

It is highly expected that partially shaded condition (PSC) occurs due to the moving clouds in a large photovoltaic (PV) generation system (PGS). Several peaks can be seen in the P-V curve of a PGS under such PSC which decreases the efficiency of conventional maximum power point tracking (MPPT) methods. In this paper, an adaptive neuro-fuzzy inference system (ANFIS) is proposed based on particle swarm optimization (PSO) for MPPT of PV modules. After tuning the parameters of the fuzzy system, including membership function parameters and consequent part parameters, to obtain maximum power point (MPP), a DC/DC boost converter connects the PV array to a resistive load. ANFIS reference model is used to control duty cycle of the DC/DC boost converter, so that maximum power is transferred to the resistive load. Comparing the proposed method with PSO alone method and firefly algorithm (FA) alone shows its efficacy and high speed tracking of MPP under PSC. Due to the fact that these optimization algorithms have online applications, the convergence time of the algorithms is very important. The simulation results show that the convergence time for the proposed ANFIS-based method is lower than 0.15 second, while it is nearly three second for PSO and FA methods

Active magnetic bearings (AMBs) are relatively new members in bearings family. Against other bearings which support loads by forces produced by fluid film pressure or physical contact, AMBs support loads by magnetic fields without any contact with the shaft and make it to be levitated. Because of that feature, AMBs have lots of benefits in comparison with other bearings. This paper presents modelling of AMBs with one and two degrees of freedom and the necessary parameters and equations for control of them is driven. Then, a numerical method based on orthogonal functions called Direct Method for optimal control in AMBs is presented with or without inequality constraints. The approach consists of reducing the optimal control problem with a two-boundary-value differential equation to a set of algebraic equations by approximating the state and control variables. This approximation uses orthogonal functions with unknown coefficients. In addition, the inequality constraints are converted to equal constraints. The problems are solved using Legendre and Haar bases. Simulation results demonstrate the benefits of Legendre functions method in compared with those using Haar bases.

This paper deals with the problem of synchronization (anti-synchronization) of fractional nonlinear systems. Here, due to the advantages of fractional calculus and sliding mode control, we provide a new fractional order sliding mode control for synchronization (anti-synchronization) problems. So, in this paper a novel sliding surface is introduced and with and without the existence of uncertainties and external disturbances, finite-time synchronization is achieved by designing a new fractional sliding mode control. This method applied to the class of fractional order nonlinear systems and sufficient conditions for achieving synchronization/anti-synchronization are derived by the use of fractional Lyapunov theory. The method is perform on different fractional order nonlinear chaotic system which confirm the applicability of the method. Here, we bring two of them for confirmation. That is to say, to show the effectiveness and robustness of the proposal, we applied our method on two identical fractional order permanent magnet synchronous machine to verify the efficacy