Fuzzy robust nonlinear control approach for electro-hydraulic flight motion simulator

Han, Songshan; Zhang, Jiao; Wang, Chengwen

doi:10.1016/j.cja.2014.12.025

Cited by 24 publications

(6 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When right pressure is applied for the aileron control, which is a clockwise rotation of aileron and elevator controls or the right deflection of the control stick or side stick controller, the airplane's right wing banks (rolls) lower in relation to the pilot [30][31][32]. When left pressure is applied to the aileron control, which is a counterclockwise rotation of aileron and elevator controls or the left deflection of the control stick or side stick controller, the airplane's left wing banks (rolls) lower in relation to the pilot [33][34][35]. Think of this movement from the pilot's head to the pilot's left hip [36]; explaining some behavior of the flight the velocity (V) is defined by (4) as well as forces and moments ( ) by (5) and (6) [37][38][39][40].…”

Section: Problem Descriptionmentioning

confidence: 99%

Fuzzy Dynamic Adaptation of Gap Generation and Mutation in Genetic Optimization of Type 2 Fuzzy Controllers

Cervantes

Castillo

Hidalgo

et al. 2018

Advances in Operations Research

View full text Add to dashboard Cite

We propose to use an approach based on fuzzy logic for the adaptation of gap generation and mutation probability in a genetic algorithm. The performance of this method is presented with the benchmark problem of flight control and results show how it can decrease the error during the flight of an airplane using fuzzy logic for some parameters of the genetic algorithm. In this case of study, we use fuzzy systems for adapting two parameters of the genetic algorithm to improve the design of a type 2 fuzzy controller and enhance its performance to achieve flight control. Finally, a statistical test is presented to prove the performance enhancement in the application using fuzzy adaptation in the genetic algorithm. It is important to mention that not only is this idea for control problems but also it can be used in pattern recognition and many different problems.

show abstract

Section: Problem Descriptionmentioning

confidence: 99%

Fuzzy Dynamic Adaptation of Gap Generation and Mutation in Genetic Optimization of Type 2 Fuzzy Controllers

Cervantes

Castillo

Hidalgo

et al. 2018

Advances in Operations Research

View full text Add to dashboard Cite

show abstract

“…In addition to fluid regulation, non-linear hydraulic movements may also affect their work and function. These non-linear characteristics arise as a result of fluid flow, leakage, saturation, friction, and external disturbances [4].…”

Section: Introductionmentioning

confidence: 99%

“…The non-linear characteristics of this system were approximated by a linear model at a certain value. The linear actuator model could not be directly designed by the controller because of its high order [4]. Order reduction using the order system 1 st approach with a time delay was executed first.…”

Section: Introductionmentioning

confidence: 99%

Design of a Fractional Order PID Controller for Electric Hydraulic Actuator

Atsari

Halim

2021

KINETIK

View full text Add to dashboard Cite

Electric hydraulic actuators are more used especially in industries that demand high levels of accuracy. A common problem with this type of actuator is consistency in fluid flow control. PID controllers can accelerate the achievement of defined output values, eliminate offsets, and reduce maximum overshoots but result in considerable errors. Therefore, it is necessary to design controllers that can reduce errors significantly. In this research, a Fractional Order PID controller is developed to reduce maximum overshoots and steady state. Unlike conventional PID controllers that have three parameters, in the Fractional Order PID controller, there are extra two parameters of the λ and μ. The parameters were selected using the Ziegler Nichols method with a 1st order approach with a delay time. Meanwhile, the λ and μ parameters were selected the best value to make the system response better. The results of the design of the Fractional Order PID controller were evaluated using matlab simulation. The simulation results showed that the Fractional Order PID controller was able to reduce the steady state error response by 0.5 %, and the maximum overshoots by 17.4 %. From this result, it can be noted that the Fractional Order PID controller is better than conventional PID.

show abstract

“…Since the assistant of the Fuzzy Logic control approach applied to the PID controller is proven to be performed better [7], therefore, the important properties of the Fuzzy Logic will be used to tuned the PID controller to obtain an optimal result for the EHS system that dealing with large amount of parameter variation [26].…”

Section: Fuzzy Tunermentioning

confidence: 99%

“…Due to its capabilities, the hydraulic system has been used in many applications such as power system [4], braking systems [5], manufacturing system [6], flight simulation [7,8], and cranes [9][10][11]. The low input power is converted into a high torque movement that used to control hydraulic applications.…”

Section: Introductionmentioning

confidence: 99%

An Electro-Hydraulic Servo with Intelligent Control Strategy

Mohammed

Soon

Ghazali

et al. 2018

MATEC Web of Conferences

View full text Add to dashboard Cite

Abstract. Versatile engineering applications have been developed to assist, reduce, and avoid human being from any heavy or harmful manufacturing processes. The gradually increased demand in force and position controls have simultaneously increased the usage of Electro-Hydraulic Servo (EHS) system. However, the time varying characteristics such as high-speed, outburst starting and stopping dynamic have led the EHS system to suffer from uncertainties and nonlinearities effects. Therefore, in order to enhance the performance of an EHS to surmount the uncertain and nonlinear effects, a hybrid Fuzzy-PID control strategy is developed which particularly improve the accuracy of the system by enhancing the control performance during the positioning tracking. By measuring the performance of the proposed control approach, the transient response and steady-state analysis will be performed which taking linear and intelligent control strategies as the references in the assessment process. The finding indicates the capability of a hybrid Fuzzy-PID controller in reducing the control effort applied to the EHS system.

show abstract

Fuzzy robust nonlinear control approach for electro-hydraulic flight motion simulator

Cited by 24 publications

References 20 publications

Fuzzy Dynamic Adaptation of Gap Generation and Mutation in Genetic Optimization of Type 2 Fuzzy Controllers

Fuzzy Dynamic Adaptation of Gap Generation and Mutation in Genetic Optimization of Type 2 Fuzzy Controllers

Design of a Fractional Order PID Controller for Electric Hydraulic Actuator

An Electro-Hydraulic Servo with Intelligent Control Strategy

Contact Info

Product

Resources

About