International Journal of Industrial Electronics, Control and Optimization
Volume:3 Issue: 4, Summer 2020

In this paper, a fault location approach is presented by using Whale Optimization Algorithm (WOA) strategy in two terminal transmission feeder. Also, Grey wolf Optimization (GWO) method is discussed. From both ends, affording the preparatory data for proposed strategies voltages and currents from both ends are measured. Several types of faults and simulations are considered in this paper and the objective function identifies the fault location with a high accuracy, correctness in a short time. Meanwhile, based on distributed model the line, the fault location is defined and since the optimization algorithm do not utilize compressed model of the line, the accuracy of the calculation is high. WOA based optimization method results in a notable reduction in the computational time. Accurate and timely location of the source of the fault greatly facilitates the job of the repair crew. This is the benefit of the proposed technique. Almost in all the cases, the accuracy of proposed procedure is very high and the error is kept below 1%.

This paper, proposes an approximate analytical method to solvea class of optimal control problems. This method is an enhancementof the variational iteration method (VIM) which is called modified variational iteration method (MVIM) and eliminates all additional calculations in VIM, thus requires less time to do the calculations. In thisapproach, first, the optimal control problem is converted into a non-linear two-point boundary value problem via the Pontryagins maximum principle, and then we applied the MVIM method to solve this boundary value problem. This suggested method is suitable for a large class of non-linear optimal control problems that for the non-linear part of the problem, we used the Taylor series expansion. In the end, three examples are provided to demonstrate the simplicity and efficiency of the method. The numerical results of the proposed method versus other methods are presented in tables. All calculations were carried out using Mathematica software.

Maximum Power Point Tracking (MPPT) is an important concept for both uniform solar irradiance and Partial Shading Conditions (PSCs). The paper presents an Improved Salp Swarm Algorithm (ISSA) for MPPT under PSCs. The proposed method benefits a fast convergence speed in tracking the Maximum Power Point (MPP), in addition to overcoming the problems of conventional MPPT methods, such as failure to detect the Global MPP (GMPP) under PSCs, getting trapped in the local optima, and oscillations around the MPP. The proposed method is compared with original algorithms such as Perturbation and Observation (P&O) method (which is widely employed in MPPT applications), Differential Evolutionary (DE) algorithm, Particle Swarm Optimization (PSO), and Firefly Algorithm (FA). The obtained results show that the proposed method can detect and track the MPP in a very short time, and its accuracy outperforms the other methods in terms of detecting the GMPP. The proposed ISSA algorithm has a higher speed and the convergence rate than the other traditional algorithms.

In this paper, a novel model-free control scheme is developed to enhance the tracking performance of robotic systems based on an adaptive dynamic sliding mode control and voltage control strategy. In the voltage control strategy, actuator dynamics have not been excluded. In other words, instead of the applied torques to the robot joints, motor voltages are computed by the control law. First, a dynamic sliding mode control is designed for the robotic system. Then, to enhance the tracking performance of the system, an adaptive mechanism is developed and integrated with the dynamic sliding mode control. Since the lumped uncertainty is unknown in practical applications, the uncertainty upper bound is necessary in the design of the dynamic sliding mode controller. Hence, the lumped uncertainty is estimated by an adaptive law. The stability of the closed-loop system is proved based on the Lyapunov stability theorem. The simulation results demonstrate the superior performance of the proposed adaptive dynamic sliding mode control strategy.

A direct torque control (DTC) controlled induction motor drive is presented in this paper. Quantization errors of current and voltage measurements are simulated and considered. To reduce the average quantization error and other offset errors of current and voltage measurement and eliminating the increasing integrator errors, a random dither signal is added to the truncating analog to digital converter (ADC) outputs. In this method, the analog to digital converter (ADC) mean error is reduced to zero and therefore integrator output error is mitigated. Proposed quantization method can improve the digital converter result, thus this method can decrease the current measurement result. Proposed quantization method can improve the digital converter result, thus this method can decrease the current measurement result. Thus, the torque and flux ripple were be decreased. Proposed ditter injection method can be used in Digital signal processor (DSP) or FPGA implemented applications. Experimental results show the performance of proposed method.

Generalized Unified Power Flow Controller (GUPFC) is a member of the flexible alternating current transmission system (FACTS) devices family that operates based on voltage source converter (VSC) and is known as the most efficient FACTs device. GUPFC can control the voltage of one bus and the active and reactive power flows on at least two transmission lines with equal voltage levels. This paper presents the mathematical modeling of power injection by GUPFC for the first time. Besides, the accurate design and details of the control system for series and shunt converters of a GUPFC, along with a new mathematical function for pulse generation based on a 48-pulse VSC when the GUPFC is placed in the middle point of a parallel transmission line, are presented in this study. The power injection modeling introduced in this paper is very useful and efficient in Newton-Raphson power flow studies and in modeling different parts of the control system and power electronics converter in dynamic and transient studies. The modeling is implemented in MATLAB/Simulink for a 400 km, 230 kV, and 60 Hz nominal frequency double-circuit transmission line. The satisfactory results provided in the simulations section of the paper verify the validity and accurate performance of the proposed model.

This work deals with minimizing fluctuations of propulsion force and improving the motion quality in a linear switched reluctance motor. In order to minimize the jerks in the moving part of the motor, a new profile has been used to generate an appropriate reference speed profile. The results indicate that at speed 0.5 m/s, the motor reaches its command speed at the proposed time while, using conventional speed profile it takes almost 1.4 times the desired time. In order to control the speed and incease the motion quality, a simple fuzzy logic system has been used which is able to overcome the uncertainties problem in nonlinear systems. The fuzzy control system can regulate the motor performance so that it tracks the reference speed with minimum error and fluctuation. To illustrate the performance of the fuzzy method, a conventional PI method along with a model reference adaptive control (MRAC) strategy have been applied to the motor and the obtained results for three control methods have been compared. Speed overshoot using conventional PI method is about 20 percent of the final speed while this is about 6 percent for fuzzy and MRAC methods. The system is designed and its efficiency is shown through simulation and experimental tests in different performance situations . The obtained results confirm that the fuzzy strategy outperforms other methods.

This paper presents a new solution method to efficiently handle non-convexity stemmed from valve points in the economic load dispatch problem. The proposed solution technique integrates both the advantage of fast solution algorithms of linear programming and powerful solution techniques of nonlinear programming to find the global solution. In the first step of the proposed solution framework, non-convex terms are replaced by some linear segments and the new linear model solved by modern fats algorithms. In the second step, a nonlinear programming algorithm as a powerful local search algorithm solves the original non-convex model to improve the solution obtained in the previous step. By exploiting the main strength of linear and nonlinear programming algorithms, the proposed solution approach can quickly converge to nearly the global solution method. By experimental results on three test cases with different sizes, we show that the presented method outperforms the other algorithms published in the literature in the quality of the solution.

This article aims to derive new sufficient conditions to guarantee the stability of piecewise affine systems with time-varying delay (PWA-TVD). The set of delay-dependent linear matrix inequality (LMI) describes the novel stability criteria. This approach considers the PWA-TVD system with a time-delayed state-dependent switching signal. The newly suggested Lyapunov-Krasovskii functional (L-K-F) and improved estimation of its derivative have a crucial role in decreasing the complexity and conservatism of the proposed stability results. The suggested L-K-F belongs to the current and time-delayed states, the integral of the states over the time-varying delay, and time derivation of the states. A new inequality was used to obtain an upper bound (UB) for the time derivation of the Lyapunov functional. Then based on this UB, less conservative results are achieved. The theoretical results are applied to the numerical examples. The results confirm the effectiveness of the presented method. The conservative index is the maximum admissible UB of time delay.

This paper presents a novel optimal impedance voltage-controller for Electrically Driven Lower Limb Rehabilitation Robots (EDLR). To overcome the dynamical complexities, and handle the uncertainties, the proposed method employs an expected forward model of the actuator. The difference between this model’s output and the actual output represents the existing value of lamped uncertainty. A voltage-controller is designed based on this uncertainty estimator, which compensate for the uncertainties. Parameters of the controller have been optimized using genetic algorithms. Key contributions of this paper are I) estimation of the uncertainty by the expected model’s output, II) overcoming the changes in motor parameters, III) introducing a class of closed-loop system termed as “Repeatable”, and IV) designing an optimal impedance voltage-controller that is non-sensitive to the parameter variations. Significant merits of the approach are swift calculations, efficiency, robustness, and guaranteed stability. Furthermore, the simplicity of design, ease of implementation and model-free independent joint structure of the approach are noticeable. The method is compared with an adaptive robust sub-controller and a Taylor-series-based adaptive robust controller, through simulations in passive range of motion and active assistive rehabilitation exercises. The results show the superiority of the proposed method in tracking performance and the time of calculations.

The AC/DC converter is one of the popular power electronic converters in industrial applications such as in the railway, power supply systems and electric vehicle. In this paper, a three-phase controllable rectifier is considered and its linear model is extracted. Because of MPC controllers benefits, the continuous control set model predictive controller (CCs-MPC) is designed for controlling this rectifier output DC voltage. By considering rectifier dynamic response, the suitable criteria to choice the model predictive controller parameters such as sampling time, prediction horizon and control horizon is proposed. In experimental implantation the computing burden of microcontroller is limit therefore the reaching to optimal and minimum complexity in algorithms implantation is vital problem. In other words by using these proposed criteria for selection of sample time, prediction and control horizon the tradeoff between computational burden, system performance and dynamic stability is made. When using designed MPC controller, the rectifier and grid performance such as total harmonic distribution (THD), power factor (PF) and output voltage ripple have acceptable value. This controller can eliminated the effect of heavy load change on rectifier performance which is very common problem in indusial system. Also, this controller stability guaranteed is checked by using the dual-mode method. The simulation results are validated by using MATLAB software and showing the designed controller performance.

Based on the recent Internet advances, congestion control is considered as an important issue and has spurred a significant amount of research. In this study, second-order sliding mode control is used to adjust the average queue length and maintain the closed-loop system performance. The control law is obtained in two steps. First, the nonlinear state-space form of the network is extracted based on state variables as the average queue length and congestion window size. Then, the proportional-Integrator-derivative and proportional- derivative sliding surface are defined according to the tracking error. Also, in order to avoid chattering, the derivative of the sliding surface is considered and the closed-loop system stability is investigated based on Lyapunov theory. The proposed scheme renders good tracking specifications and closed-loop system robustness. The simulation results show that the proposed methods outperform proportional integral (PI) and proportional integral derivative (PID) schemes. Also, robustness to disturbances increases and chattering and transient response degradation are avoided.