The problem of timedelaycompensation in deadbeatcontrol for powerconverters are considered but not solved systematically, by far. A linear phase-lead compensation solution is successfully employed in repetitive control systems to compensate the timedelay -. However, it is impractical to be adopted in the conventional deadbeatcontrol frame due to its incausal lead-time item. A state estimator is adopted for compensation of computational delay . Also focused on this problem, another simple design method of two steps forward prediction approach is proposed in the frame of model predictive control , , . In these solutions, computational delay effects are effectively removed and control accuracy is prominently improved. However, as mentioned above, apart from computational delay, many other factors lead to the delay problem in practical systems. In these cases, the above mentioned approaches are not suitable and fail to achieve satisfying control performance. Therefore, a universal delaycompensation approach for the deadbeatcontrol schemes should be investigated in practical applications.
Sahu et al.  have outlined around the design and style as well as effectiveness evaluation regarding Differential Evolution (DE) algorithm based parallel 2-Degree Freedom of Proportional-Integral-Derivative (2-DOF PID) controller for Load Frequency Control (LFC) of interconnected power system process. The planning issue has been formulated as an optimization issue and DE has been currently employed to look for optimal controller parameters. Standard as well as improved aim features have been used for the planning goal. Standard aim features currently employed, which were Integral of Time multiplied by Squared Error (ITSE) and Integral of Squared Error (ISE). To be able to additionally raise the effec- tiveness in the controller, some sort of improved aim operate is derived making use of Integral Time multiply Absolute Error (ITAE), damping ratio of dominant eigenvalues, settling times of frequency and peak overshoots with appropriate weight coefﬁcients. The particular ﬁneness in the recommended tech- nique has become conﬁrmed by simply contrasting the results with a lately published strategy, i.e. Craziness based Particle Swarm Optimization (CPSO) for the similar interconnected electric power process. Further, level of sensitivity evaluation has been executed by simply varying the machine details as well as managing load conditions off their nominal valuations. It is really observed which the recommended controllers are quite powerful for many the system parameters as well as man- aging load conditions off their nominal valuations.
which have time delays in sensor to controller and controller to actuator paths. Using the linear model of the plant, they obtained a sequence of control predictions, and then it was transmitted to the actuator, and the actuator chose the most appropriate data to compensate for the timedelay. Hu et al.  used a fuzzy control algorithm and Smith method to compensate for the timedelay in networked control systems. They provided a fuzzy adaptive PID controller with Smith’s prediction. Using a discrete nonlinear model of the plant and taking advantage of Lyapunov-Krasovskii stability theorem, Peng et al. in  derived the maximum allowable delay bound and the feedback gain of a controller by solving a set of linear matrix inequalities. In , the prediction method based on MPC model for linear systems to compensate for the effect of timedelay and data dropout was studied. The authors of  dealt with the compensation for data dropout in the linear networked control system using the fractional-order Kalman filter method. Fulto et al.  utilized two methods of neutral and extended Kalman filters to compensate for the data dropout in nonlinear systems and compared their performance with each other. Khan et al.  investigated the positioning and tracking performance of extended Kalman filter in wireless sensors network. Further, localization performance under varying number of sensors was also evaluated.
he first step towards the development of new testing procedures for power components was demonstrated with the development of hardware-in-the-loop simulation (HIL), which is able to merge the two traditional testing procedures (computer simulation and hardware testing) by interfacing the software simulation with the real hardware under test. Mainly controller devices are used as testing devices for HIL simulation due to the fact that they only need low power and voltage signals to be exchanged and consequently this procedure is also called controller-hardware- in-the-loop (C-HIL) simulation. Since just low level signals are exchanged between the software simulation and the hardware under test, this procedure is not valid for power components such as motors, generators or powerconverters that require higher levels of power to be exchanged. Hence, in order to achieve an improvement in cost, time, flexibility, risk, and accuracy of the testing methodology for these power components further development was required. The solution for HIL simulation with power components was achieved by the addition of a power interface between the software simulation and the hardware under test, as shown in Fig.1. The
Due to its complexity and diversity, many systems, such as communication systems, power systems, biological systems, network transmission systems, always inevitably show hysteresis: the rate of change of the current state is not only related to the state of the cur- rent moment, but it also depends on the state of a certain moment or a certain period of time in the past. This property of the systems is called timedelay, and researchers have introduced diﬀerential equations with timedelay to describe and study the time-delay system. Especially, the dynamics of predator–prey (PP) systems with delay have been pro- posed and studied extensively. Many researchers have considered the impact of the past states of biological systems on the present and the future, i.e. incorporating timedelay into biological models to describe resource regeneration time, maturation time, reaction time, capturing time, feeding time, gestation period [27, 28]. On the other hand, time-delay bi- ological systems have more complex and richer dynamic behaviors: delays can cause the loss of stability and can induce periodic solutions (Hopf bifurcation), chaos and various oscillations [29–34].
function expansion in series of exponentials and definition of n th order derivative by operating term-by-term, while Riemann introduced the definite integral applicable to power series with non-integer exponents. Later, Grunwald and Krug unified the results of Liouville and Riemann, with the first application of fractional calculus dating from 1823. Heav- iside developed symbolic methods for solving linear dif- ferential equations of constant coefficients, while Weil and Hardy defined the differ-integral operator properties and Riesz extended the result to multivariable functions, etc. . In the last decades, the number of applications for fractional- order calculus has been growing exponentially, mainly in the fields of control engineering, signal processing and system theory. The main advances were made by Bode’s ideal loop transfer function, followed by Manabe’s results on frequency and transient response of the non-integer integral and its application in control. The first occurrence of fractionalorder controller may be attributed to Oustaloup, who introduced and demonstrated the superiority of the Commande Robuste dOrdre Non Entier (CRONE) controller. The generalization of the integer order proportional-integrative-derivative (PID) controller to fractionalorder has been proposed by Podlubny . The fractionalorder basic control actions, proportional, integral and derivative, add more flexibility to the set of performance specifications the closed loop system is able to fulfill. This is mainly due to the extra tuning parameters of the fractionalorder PID (FOPID): the fractionalorder of integra- tion and the fractionalorder of differentiation. Even though the FOPID represents the most common fractionalordercontrol algorithm, other types of fractionalorder controllers have been designed, as it will be indicated later in this paper. Review papers focusing on the use of fractional calculus in control engineering have been published recently such as – and provide an insight into fractionalordercontrol of different types. Analytic, numerical and rule-based tuning methods for fractionalorder PID controllers only has also been published . Some of these methods can also be used to controltimedelay systems.
This paper studies the ﬁnite-time stability of fractional singular time-delay systems. First, by the method of the steps, we discuss the existence and uniqueness of the solutions for the equivalent systems to the fractional singular time-delay systems. Furthermore, we give the Mittag-Leﬄer estimation of the solutions for the equivalent systems and obtain the suﬃcient conditions of the ﬁnite-time stability for the original systems.
using a fixed FROH in the closed loop behavior and, it investigates the performance of two different multi-model schemes. It is supported by the idea that FROH with intermediate adaptation rate modifies the location of the zeros of the discrete transfer function with respect to those obtained from the use of a zero-order-hold (ZOH) or a first-order-hold (FOH). Two possible advantages are: a) the stability degree of stable zeros can be improved so that some of them can be better cancelled when implementing a model-following control design while improving the transient closed- loop behavior; b) the discrete control can better accommodate the rippling effect in-between any two consecutive sampling instants when applying a discrete-timecontrol to a continuous-time plant. The reason is that there is there is a kind of practical interpolation in continuous time from measured data in-between two consecutive such samples due to the structure of the FROH what allows to accommodate the control law in continuous time while just using discrete-time data. 18,19,20 As a result, the controller can lead, for example, to produce better surface finish and maintenance of the tool and machine tool components and to minimize wear of the tool while avoiding or minimizing electrical ripple. Multi-model schemes are also useful, for instance, when the system works in different states governed by different equations from the milling case or, to modify the closed-loop structure in one working point achieving best tracking performance. So, the algorithm methodologies can be useful when the holistic control of the milling process is taking into account in order to achieve better surface finish or to deal with some kind of intrinsic non-linearity. Also, FROH has potential benefits when dealing with ramp form milled parts or to improve transient responses leading to further potential benefits.
In distribution systems, there will be sudden increase or decreases in the load similar to nonlinear load .The load draws non-sinusoidal currents from the AC mains and these causes the load harmonics and reactive power, and excessive neutral currents that pollute power systems. Most of the power quality issues are created by nonlinear characteristics and fast switching of power electronic devices. A single distribution generation interfacing converters are generally used for harmonic compensation in DG but this may cause amplification of supply voltage harmonics when the system is connected to a sensitive load. In this paper we proposed a compensation strategy in which to shunt interfacing converters are used, first one for voltage harmonic suppression and the second one for current harmonic suppression that resulted due to the interaction between the first interfacing converter and the local nonlinear load
III. P ROTECTION OF D ISTRIBUTED G ENERATION We use the impedance measurement to identify the proximity of a grid fault to PEE. This measurement is used to decide whether PEE should ride through certain remote faults to avoid nuisance trips. Islanding may also be detected. Consider the system in Fig. 6 in which a small power system is defined to be a “protected zone” in a larger power system. Details of the system parameters, which are based on a medium voltage distribution system, are given in the Appendix. Within the zone there are distributed generation and power electronic equipment – for example an active filter, a grid interface for a wind turbine, or photovoltaic system – which are connected at the point of measurement (POM).
Stability analysis of nonlinear systems is necessary to design a controller. Several works have investigated stability analysis of nonlinear systems by means of fractional calculus [26-30]. In , fractional generalization of concept of stability was considered. In , a definition for Mittag-Leffler stability and fractional Lyapunov direct method were presented. In , stability analysis of FO nonlinear systems was derived using the Lyapunov direct method with Mittag-Leffler stability. In , stability of fractional differential systems based on the conformable fractional derivatives was studied. However, there are very few papers considering modelling of the nonlinear systems with conformal FO definition [29,30]. Therefore, application of the conformable FO operators in the design of FO controller is an open area. Accordingly, for the first time, in this paper, a FO sliding mode control is designed for a class of conformable fractionalorder chaotic system using the conformable fractional derivative and the superiority of the proposed controller is shown. Having these facts in mind, the main contributions of this paper in comparison with previous researches are as follows. A novel FO manifold using conformable FO operators is proposed to control chaotic systems in the presence of uncertainties and disturbances. The conformable FO operator as an interesting definition is applied in designing of the FO sliding mode controller. Based on conformable FO operators, the stability of the controller is derived using the Lyapunov direct method. The main advantage of the proposed control method is fast convergence speed with together less chattering and complexity in calculations.
ower hardware-in-the-loop (PHIL) simulation is an ex- tension of the widely known hardware-in-the-loop (HIL) simulation concept. However, in contrast with the most common procedure of HIL called controller hardware-in-the- loop (CHIL), where the hardware under test (HUT) is a con- troller that only exchanges control signals with the simulated system, PHIL allows the testing of power components by exchanging power with the simulated system through the power interface. The power interface electrically couples and converts the low voltage/power signals of the real time simu- lator (RTS) into high voltage/power signals going into the HUT. The HUT responds to the applied signal (current or voltage), and the measurement of this response is fed back (by the power interface or an external measurement unit) to the RTS closing the loop, and therefore creating a simulation system that ideally would match with the real one. This struc- ture of a PHIL simulation is shown in Fig. 1. However, stabil- ity and accuracy issues exist when an interface is used, this is due to the introduced error during the simulation and amplifi- cation stages, and also to additional components introduced to compensate for the time-delay or for a stability improvement [1-4].
This article discusses the control system of fractional endpoint variable variational problems. For this problem, we prove the Euler-Lagrange type necessary conditions which must be satisﬁed for the given functional to be extremum. Finally, one example is provided to show the application of our results.
Grünwald–Letnikov sense. Stability analysis of ﬁxed points is studied. Corresponding fractional optimal control problem, with time delays in both state and control variables, is formulated and studied. Two simple numerical methods are used to study the nonlinear fractionaldelay optimal control problem. The methods are standard ﬁnite diﬀerence method and nonstandard ﬁnite diﬀerence method. Comparative studies are implemented, it is found that the nonstandard ﬁnite diﬀerence method is better than the standard ﬁnite diﬀerence method.
Fractional diﬀerential and integral equations have recently been applied in various areas of engineering, science, ﬁnance, applied mathematics, bio-engineering and others. There has been a signiﬁcant development in ordinary and partial fractional diﬀerential equations in recent years; see the monographs of Abbas et al. , Baleanu et al. , Kilbas et al. , Lakshmikantham et al. , Podlubny , and the references therein.
Abstract - The power electronic converters plays crucial role in conversion and control of the electrical power. The production of solar energy is based on the idea of converting a type of energy mostly solar energy into electrical energy. The most appealing renewable energy source is photovoltaic which transform the solar energy into DC electrical energy. Power electronics converters are used to control frequency and magnitude of the current resultant from the conversion between energies. The objective of this paper is to model and control of transformer-less grid connected PV system with Hysteresis controller which can be used to supply the electric power to utility grid. This system uses two stage conversion process. DC to DC stage which utilizes MPPT technique to extract the maximum power. DC to AC which used to control inverter output by using hysteresis Current controller. The problem of maximum power transferring is enhanced by using Incremental conductance algorithm and phase locked loops are utilized in conjunction to make supply in synchronization with the grid which reduces the two problems described. The studied system is modeled and simulated in the MATLAB/SIMULINK environment.
However, to the best of the authors’ knowledge, to this day, still less scholars consider the adaptive impulsive synchronization of delayfractional-order chaotic systems. Motivated by the above works, the adaptive impulsive synchronization for a class of fractional-order chaotic systems with an unknown Lipschitz constant and timedelay is discussed. The rest of this paper is organized as follows: In Section 2, some preliminaries of fractional derivative are briefly introduced. A new adaptive impulsive synchronization method of delayfractional-order chaotic systems is proposed in Section 3, based on the theory of Lyapunov stability and impulsive differential equations. Finally, conclusions are addressed in Section 4.
share is expected to double in the next 15 years, partly due to the rapid growth of variable renewable energy from solar photo voltaics and wind. This IRENA/IEA-ETSAP Technology Brief provides an overview of the main performance and costs of technologies that are used to support renewable energy grid integration, an overview of the shares of variable renewable energy across the world, and existing operational experiences in continental and island systems. There are several technology options available that can help integrate variable renewable energy into power systems. Furthermore, new advances in wind and solar technologies allow them to be used over a wider range of conditions. In the longer run, however, power systems with high shares of variable renewable power generation will require a re-thinking the traditional designs, operations, and planning practices from a technical and an economical point of view.Two immediate applications for innovative technologies and operation modes for the integration of high shares of solar photovoltaics and wind are in mini-grids and islands. Furthermore, any economic analysis of the transition towards a renewables -based system should always consider the total system costs, including social and environmental benefits
The fractional calculus is the area of mathematics that handles derivatives and integrals of any arbitrary order (fractional or integer, real or complex order).Although the concept of the fractional calculus was discussed in the same time interval of integer order calculus, the complexity and the lack of applications postponed its progress till a few decades ago. During the last few decades, most of the dynamical systems based on the integer-order calculus have been modified into the fractionalorder domain due to the extra degrees of freedom and the flexibility which can be used to precisely fit the experimental data much better than the integer- order modeling and fractional calculus has become a powerful tool in describing the dynamics of complex systems which appear frequently in several branches of science and engineering. Therefore fractional differential
For analogy, the performance of controller tuning methods is compared for variations in load and set point when they undergo a step change of unit magnitude. L/T ratio is a signifi- cant factor which affects the controller performance and sensi- tivity of the feedback control system. The effect of L/T ratio on different tuning methods was studied by varying timedelay L so that the ratio L/T varies from 0.1 to 2 covering lag dominant, balanced and delay significant processes. The simulations were carried out on different FOPTD processes. The main reason for varying the L/T ratio is that it affects the robustness of control- ler and performance of the closed loop system. For each varia- tion of L/T, new controller settings are calculated and closed loop response (both servo and regulatory) is observed, thus recording IAE, TV and M s . The trends of the performance