Frequency stability analysis with fuzzy adaptive selfish herd optimization based optimal sliding mode controller for microgrids

Author(s):  
Narendra Kumar Jena ◽  
Subhadra Sahoo ◽  
Binod Kumar Sahu ◽  
Kanungo Barada Mohanty

Abstract This article articulates the frequency control in an isolated microgrid (MG) under a centralized secondary controller. The penetration of distributed generators (DGs) which are weather dependant, and some of them are inertia less cause the instability in the MG. Besides this, unusual/abrupt load change, communication delay, and parameter change uncertainties make the MG more unstable. So, to restore the stability of the MG a sliding mode controller (SMC) is employed. The design of the SMC is carried by selfish herd optimization (SHO) algorithm. To validate the performance of SHO-SMC controller, it is compared with the results obtained by GOA-FOPID-(1+PI), SHO-PID, SHO- FOPID, and SHO-FOPID-(1+PI) controllers. Further, to establish an ameliorated dynamic response of the MG, SHO is modified by applying fuzzy logic named as fuzzy adaptive SHO (FA-SHO). In addition to this, in a two area MG, the potential of SHO/FA-SHO SMC controllers over SHO-SMC, and SHO/FA-SHO FOPID-(1+PI) controllers has been examined. Finally, with some crucial intermittent uncertainties like abrupt load change, time delay, and parameter variation, the robustness of the proposed controller is established.

Author(s):  
Naser Esmaeili ◽  
Reza Kazemi ◽  
S Hamed Tabatabaei Oreh

Today, use of articulated long vehicles is surging. The advantages of using large articulated vehicles are that fewer drivers are used and fuel consumption decreases significantly. The major problem of these vehicles is inappropriate lateral performance at high speed. The articulated long vehicle discussed in this article consists of tractor and two semi-trailer units that widely used to carry goods. The main purpose of this article is to design an adaptive sliding mode controller that is resistant to changing the load of trailers and measuring the noise of the sensors. Control variables are considered as yaw rate and lateral velocity of tractor and also first and second articulation angles. These four variables are regulated by steering the axles of the articulated vehicle. In this article after developing and verifying the dynamic model, a new adaptive sliding mode controller is designed on the basis of a nonlinear model. This new adaptive sliding mode controller steers the axles of the tractor and trailers through estimation of mass and moment of inertia of the trailers to maintain the stability of the vehicle. An articulated vehicle has been exposed to a lane change maneuver based on the trailer load in three different modes (low, medium and high load) and on a dry and wet road. Simulation results demonstrate the efficiency of this controller to maintain the stability of this articulated vehicle in a low-speed steep steer and high-speed lane change maneuvers. Finally, the robustness of this controller has been shown in the presence of measurement noise of the sensors. In fact, the main innovation of this article is in the designing of an adaptive sliding mode controller, which by changing the load of the trailers, in high-speed and low-speed maneuvers and in dry and wet roads, has the best performance compared to conventional sliding mode and linear controllers.


2012 ◽  
Vol 22 (3) ◽  
pp. 315-342 ◽  
Author(s):  
Samir Zeghlache ◽  
Djamel Saigaa ◽  
Kamel Kara ◽  
Abdelghani Harrag ◽  
Abderrahmen Bouguerra

Abstract In this paper we present a new design method for the fight control of an autonomous quadrotor helicopter based on fuzzy sliding mode control using backstepping approach. Due to the underactuated property of the quadrotor helicopter, the controller can move three positions (x;y; z) of the helicopter and the yaw angle to their desired values and stabilize the pitch and roll angles. A first-order nonlinear sliding surface is obtained using the backstepping technique, on which the developed sliding mode controller is based. Mathematical development for the stability and convergence of the system is presented. The main purpose is to eliminate the chattering phenomenon. Thus we have used a fuzzy logic control to generate the hitting control signal. The performances of the nonlinear control method are evaluated by simulation and the results demonstrate the effectiveness of the proposed control strategy for the quadrotor helicopter in vertical flights.


Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3091 ◽  
Author(s):  
Pedro Ponce ◽  
J. Antonio Rosales ◽  
Arturo Molina ◽  
Hiram Ponce ◽  
Brian MacCleery

Electric direct-current (DC) drives based on DC motor are extremely important in the manufacturing process, so it must be crucial to increase their performance when they are working on load disturbances or the DC motor’s parameters change. Usually, several load torque suddenly appears when electric drives are operating in a speed closed-loop, so robust controllers are required to keep the speed high-performance. One of the most well-known robust strategies is the sliding mode controller (SMC), which works under discontinue operation. This controller can handle disturbances and variations in the plant’s parameters, so the controller has robust performance. Nevertheless, it has some disadvantages (chattering). Therefore, this paper proposed a fuzzy logic controller (FLC) that includes an artificial organic network for adjusting the command signal of the SMC. The proposed controller gives a smooth signal that decrements the chattering in the SMC. The stability condition that is based on Lyapunov of the DC motor is driven is evaluated; besides, the stability margins are calculated. The proposed controller is designed using co-simulation and a real testbed since co-simulation is an extremely useful tool in academia and industry allows to move from co-simulation to real implementation in short period of time. Moreover, there are several universities and industries that adopt co-simulation as the main step to design prototypes. Thus, engineering students and designers are able to achieve excellent results when they design rapid and functional prototypes. For instance, co-simulation based on Multisim leads to design directly printed circuit boards so engineering students or designers could swiftly get an experimental DC drive. The experimental results using this platform show excellent DC-drive performance when the load torque disturbances are suddenly applied to the system. As a result, the proposed controller based on fuzzy artificial organic and SMC allows for adjusting the command signal that improves the dynamic response in DC drives. The experimental response using the sliding-mode controller with fuzzy artificial organic networks is compared against an auto-tuning, Proportional-Integral-Derivative (PID), which is a conventional controller. The PID controller is the most implemented controller in several industries, so this proposal can contribute to improving manufacturing applications, such as micro-computer numerical control (CNC) machines. Moreover, the proposed robust controller achieves a superior-speed response under the whole tested scenarios. Finally, the presented design methodology based on co-simulation could be used by universities and industry for validating and implementing advanced control systems in DC drives.


2020 ◽  
Vol 10 (11) ◽  
pp. 3719
Author(s):  
Ran Jiao ◽  
Wusheng Chou ◽  
Yongfeng Rong ◽  
Mingjie Dong

Aerial operation with unmanned aerial vehicle (UAV) manipulator is a promising field for future applications. However, the quadrotor UAV manipulator usually suffers from several disturbances, such as external wind and model uncertainties, when conducting aerial tasks, which will seriously influence the stability of the whole system. In this paper, we address the problem of high-precision attitude control for quadrotor manipulator which is equipped with a 2-degree-of-freedom (DOF) robotic arm under disturbances. We propose a new sliding-mode extended state observer (SMESO) to estimate the lumped disturbance and build a backstepping attitude controller to attenuate its influence. First, we use the saturation function to replace discontinuous sign function of traditional SMESO to alleviate the estimation chattering problem. Second, by innovatively introducing super-twisting algorithm and fuzzy logic rules used for adaptively updating the observer switching gains, the fuzzy adaptive saturation super-twisting extended state observer (FASTESO) is constructed. Finally, in order to further reduce the impact of sensor noise, we invite a tracking differentiator (TD) incorporated into FASTESO. The proposed control approach is validated with effectiveness in several simulations and experiments in which we try to fly UAV under varied external disturbances.


2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Yassine El Houm ◽  
Ahmed Abbou ◽  
Moussa Labbadi ◽  
Mohamed Cherkaoui

This paper deals with the design of a novel modified supertwisting fast nonlinear sliding mode controller (MSTFNSMC) to stabilize a quadrotor system under time-varying disturbances. The suggested control strategy is based on a modified supertwisting controller with a fast nonlinear sliding surface to improve the tracking performance. The paper suggests a simple optimization tool built-in MATLAB/Simulink to tune the proposed controller parameters. Fast convergence of state variables is established by using a nonlinear sliding surface for rotational and translational subsystems. The modified supertwisting controller is developed to suppress the effect of chattering, reject disturbances, and ensure robustness against external disturbance effect. The stability of the proposed controller (MSTFNSMC) is proved using the Lyapunov theory. The performance of the proposed MSTFNSMC approach is compared with the supertwisting sliding mode controller (STSMC) by numerical simulations to verify its effectiveness.


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