fuzzy controller

This study focuses on the design and experimental evaluation of a road excitation simulator driven by an electro-hydraulic system. The simulator is employed to create road irregularities, which are then applied to the vehicle platform during laboratory testing. To generate the desired road inputs by the simulator, a fuzzy tracking control law is developed based on expert knowledge of the system derived from displacement data obtained from a linear potentiometer transformer. The fuzzy controller utilizes the Mamdani structure to compute the required voltage for the electro-hydraulic directional valves. This controller is implemented through the LabView interface, and its performance is evaluated and compared against a proportional-integral-derivative (PID) controller under various road inputs. Experimental results from tests conducted on a fabricated platform in the laboratory demonstrate that the fuzzy method offers superior accuracy and reliability compared to the PID controller. The designed simulator is capable of generating a variety of standard road inputs for testing the vibrations of various vehicles and their cargo.

This study examines the impact of a fuzzy logic-based control strategy on managing peak power consumption in the auxiliary power unit (APU) of a hybrid electric bus. The APU comprises three components: an air compressor, a power steering system, and an air conditioning system (AC) connected to an electric motor. Initially, these components were simulated in MATLAB-SIMULINK software. While the first two were deemed dependent and independent of vehicle speed, respectively, the stochastic behavior of the steering was emulated using the Monte Carlo method. Subsequently, a fuzzy controller was designed and incorporated into the APU to prevent simultaneous operation of the three accessories as much as possible. The results of repeated simulations demonstrated that the designed fuzzy controller effectively distributed the operation of the accessories throughout the driving cycle, thereby reducing overlaps in auxiliary loads. Consequently, the APU's average and maximum power consumption exhibited significant reductions. Furthermore, through multiple simulations with an upgraded power system model integrating the new APU-controller package, it was established that the proposed strategy for managing auxiliary loads in the bus led to lower fuel consumption and emissions.

In this article, a complete model including cross-coupling of azimuth and elevation axes, the effect of axis friction, non-perpendicularity and imbalance of axes was implemented for the platform with two degrees of freedom. Since this model includes 3 loops of current, stability and tracking from the inside to the outside, it was necessary to design a suitable controller for each loop separately from the inside to the outside after linearizing the obtained model. Also, due to the presence of two channels, azimuth and elevation, it was necessary to repeat and design 3 controllers for both channels separately. Since the purpose of this article is to compare the performance of different controllers, PID, Fuzzy, Fuzzy PID and Fuzzy self-tuning controllers for both channels and all loops, their design and performance in time and frequency domains were analyzed. At the end, relative advantages of each controller according to different parameters of the system were presented in a comparative table.

This paper experimentally investigates the trafficability of a small tracked vehicle on a slope. An increase in the angle of slope inclination may divert the vehicle from its path. In other words, the deviation of the vehicle is due to a sudden increase in the yaw angle. Also, the tip-over occurs at a specific slope angle. The locomotion of the small tracked vehicle on soils with different terramechanics (such as cohesion, internal friction angle, cohesive modulus, and friction modulus) is also simulated to evaluate its slope-traversing performance. Moreover, the impact of velocity and soil type on traversing a slope is measured. The proposed yaw angle control system is modeled for controlling the yaw angle of the tracked vehicle. This controller is designed through co-simulation. It keeps the tracked vehicle at zero yaw angle to achieve straight locomotion on slopes. It is compared to the PI, PID, and fuzzy controllers. The response of this controller is faster than PI and PID controllers. A Comparison between fuzzy and proposed yaw angle controller yields almost similar responses. The mechanism of the proposed yaw angle controller is also easier to understand. The precision of the controller's performance is measured by simulating over different terrains.

DVR is one of the important Custom Power Device to compensate sag or swell of voltage in the distribution network that precision of voltage compensation depends on the ability of the PWM design, the appropriate controller and the selection of the filter parameters. Traditional controllers such as PI, PID and smart controllers such as fuzzy controller can be used to control the DVR. Fuzzy controllers are nonlinear controllers with specific structure. The fuzzy controller acts like an expert human when controlling. The disadvantage of these controllers is their inability to learn that genetic algorithms, neural networks and etc are used to solve this problem. In this paper, a genetic algorithm is used to optimize the fuzzy membership functions of the fuzzy controller.

The purpose of this paper is to design and optimize an intelligent fuzzy-logic controller for a three-degree of freedom (3DOF) artificial finger with shape-memory alloy (SMA) wire actuators. The robotic finger is constructed using three SMA wires as tendons to bend each phalanx of the finger around its revolute joint and three torsion springs which return the phalanxes to their original positions. A PID controller is designed to control the rotation of each phalanx. The gains of the controller are defined and optimized using the genetic algorithm. Finally, a fuzzy PID controller is presented to improve the performance of the system. The performance of the designed controller to achieve the desired output is simulated and also tested. The rotation of each link of both prototype robot and simulated model is measured. The experimental results show that the fuzzy controller can reach the desired angle in less time and the output signal is uniform. Moreover, the simulation results indicate that the closed-loop control system of the simulated robot is in good agreement with the prototype robot.

This paper focuses on variable speed wind turbines operation with pitch control. An advanced control strategy is proposed based on linear quadratic regulator and fuzzy controllers in order to improve the performance of the variablespeed wind turbine. The proposed controller is designed to reduce rotor speed variation and optimizing wind turbine power. Wind turbine states are estimated by using fuzzy observer. Moreover, the Takagi-Sugeno fuzzy strategy is used to regulate the rotor speed by controlling the rotation of blades. The proposed method is implemented on MATLAB software by SimWindFarm simulator. Simulation results proved that the fuzzy TS method is appropriate in improving efficiency of wind turbine. Moreover, the proposed method shows better performance compared to the PI controller.

Hybrid electric vehicles employ a hydraulic braking system and a regenerative braking system together to provide enhanced braking performance and energy regeneration. In this paper an integrated braking system is proposed for an electric hybrid vehicle that include a hydraulic braking system and a regenerative braking system which is functionally connected to an electric traction motor. In the proposed system, four independent anti-lock fuzzy controllers are developed to adjust the hydraulic braking torque in front and rear wheels. Also, an antiskid controller is applied to adjust the regenerative braking torque dynamically.  A supervisory controller, is responsible for the management of this system.  The proposed integrated braking system is simulated in different driving cycles. Fuzzy rules and membership functions are optimized considering the objective functions as SoC and slip coefficient in various road conditions. The simulation results show that the fuel consumption and the energy loss in the braking is reduced. In the other hand, this energy is regenerated and stored in the batteries, especially in the urban cycles with high start/stop frequency. The slip ratio remains close to the desired value and the slip will not occur in the whole driving cycle. Therefore, the proposed integrated braking system can be considered as a safe, anti-lock and regenerative braking system.