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Go to Editorial ManagerThis paper focuses on the vibration suppression of a half-car model by using a modified PID controller. Mostly, car vibrations could result from some road disturbances, such as bumps or potholes transmitted to a car body. The proposed controller consists of three main components as in the case of the conventional PID controller which are (Proportional, Integral, and Derivative) but the difference is in the positions of these components in the control loop system. Initially, a linear half-car suspension system is modeled in two forms passive and active, the activation process occurred using a controlled hydraulic actuator. Thereafter, the two systems have been simulated using MATLAB/Simulink software in order to demonstrate the dynamic response. A comparison between conventional and modified PID controllers has been carried out. The resulting dynamic response of the half-car model obtained from the simulation process was improved when using a modified PID controller compared with the conventional PID controller. Moreover, the efficiency and performance of the half-car model suspension have been significantly enhanced by using the proposed controller. Thus, achieving high vehicle stability and ride comfort.
The main objective of designed the controller for a vehicle suspension system is to reduce the discomfort sensed by passengers which arises from road roughness and to increase the ride handling associated with the pitching and rolling movements. This necessitates a very fast and accurate controller to meet as much control objectives, as possible. Therefore, this paper deals with an artificial intelligence Neuro-Fuzzy (NF) technique to design a robust controller to meet the control objectives. The advantage of this controller is that it can handle the nonlinearities faster than other conventional controllers. The approach of the proposed controller is to minimize the vibrations on each corner of vehicle by supplying control forces to suspension system when travelling on rough road. The other purpose for using the NF controller for vehicle model is to reduce the body inclinations that are made during intensive manoeuvres including braking and cornering. A full vehicle nonlinear active suspension system is introduced and tested. The robustness of the proposed controller is being assessed by comparing with an optimal Fractional Order PI λ D μ (FOPID) controller. The results show that the intelligent NF controller has improved the dynamic response measured by decreasing the cost function.
Reducing the dependency of the control system on communication in the microgrid increases the reliability and flexibility of an islanded microgrid. This paper presents a local secondary control approach to provide a fast response to power change and accurate frequency restoration. It is based on a control scheme that uses a secondary controller involving a time-controllable parameter for a Low pass filter. The high value of the time-varying parameter is placed to satisfy excellent performance regarding fast active power sharing, and the time-controllable parameter decreases after achieving power-sharing based on a time protocol to ensure accurate steady-state frequency restoration. This paper also describes the criteria for control parameter selection and stability analysis based on a precise modeling approach. The MATLAB environment is used to simulate and test the proposed control scheme, and the results have been obtained that show the validity and high performance of the proposed controller in terms of dynamic response to active power change and steady-state restoration under different operation conditions.
Wind Energy Conversion Systems (WECSs) have experienced significant growth in recent years.Among various types of generators employed in WECSs,Permanent Magnet Synchronous Generators (PMSGs) are an attractive choice among the wide variety of wind generators due to several advantages.The growing penetration of PMSG-based WEGSs into the worldwide electrical grid raises the concern that the failure of wind turbine generators may potentially result in the collapse of the system.This prompted several countries to adopt the Low-Voltage Ride-Through (LVRT) for wind farms.LVRT is the capability to maintain the connection between the wind farm and the grid during certain periods of voltage sag.This paper presents an efficient LVRT control strategy for a 12.0MW (6*2MW) grid-connected PMSG-based Wind Farm (PMSG-WF).The proposed strategy aims to enhance the power quality and amount of injected power to achieve the grid code requirements by integrating a Braking Chopper (BC) and a Dynamic Voltage Restorer (DVR) with the conventional structure of PMSG-WF. The detailed mathematical models for a wind turbine, PMSG, power converters, DVR system, and grid model are utilized to analyze the dynamic behavior and operation of PMSG-WF.For DVR, a PI controller is used for voltage sag mitigation to inject reactive power during grid faults, while a hysteresis controller-based BC system is utilized to keep DC-link voltage within its permissible limits.The proposed system is exposed to three scenarios of symmetrical and asymmetrical grid fault conditions (single-phase, two-phase, and three-phase faults) at the point of common coupling to evaluate its dynamic response.MATLAB/SIMULINK environment is used to validate the effectiveness of the proposed strategy during the studied scenarios.The results show the superiority of DVR in improving the voltage stability of PMSG-WF and maintaining the uninterrupted operation of the grid during different grid faults.
Hybrid electric vehicles have received considerable attention because of their ability to improve fuel consumption compared to conventional vehicles. In this paper, a series-parallel hybrid electric vehicle is used because they combine the advantages of the other two configurations. In this paper, the control unit for a series-parallel hybrid electric vehicle is implemented using a Nonlinear Model Predictive Control (NMPC) strategy. The NMPC strategy needs to create a vehicle energy management optimization problem, which consists of the cost function and its constraints. The cost function describes the required control objectives, which are to improve fuel consumption and obtain a good dynamic response to the required speed while maintaining a stable value of the state of charge (SOC) for batteries. While the cost function is subject to the physical constraints and the mathematical prediction model that evaluate vehicle's behavior based on the current vehicle measurements. The optimization problem is solved at each sampling step using the (SQP) algorithm to obtain the optimum operating points of the vehicle's energy converters, which are represented by the torque of the vehicle components.
This paper presents a method for improving the speed profile of a three phase induction motor in direct torque control (DTC) drive system using a proposed fuzzy logic based speed controller. A complete simulation of the conventional DTC and closed-loop for speed control of three phase induction motor was tested using well known Matlab/Simulink software package. The speed control of the induction motor is done by using the conventional proportional integral (PI) controller and the proposed fuzzy logic based controller. The proposed fuzzy logic controller has a nature of (PI) to determine the torque reference for the motor. The dynamic response has been clearly tested for both conventional and the proposed fuzzy logic based speed controllers. The simulation results showed a better dynamic performance of the induction motor when using the proposed fuzzy logic based speed controller compared with the conventional type with a fixed (PI) controller.