scholarly journals A Constant-Pressure Hydraulic PTO System for a Wave Energy Converter Based on a Hydraulic Transformer and Multi-Chamber Cylinder

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 241
Author(s):  
Chenglong Li ◽  
Dahai Zhang ◽  
Weijie Zhang ◽  
Xiaodong Liu ◽  
Ming Tan ◽  
...  
Keyword(s):  
Power Generation ◽  
Fuzzy Control ◽  
Control Strategy ◽  
Constant Pressure ◽  
Fuzzy Controller ◽  
Electrical Energy ◽  
Power Circuit ◽  
Hydraulic Transformer ◽  
The Stability ◽  
Transformer Ratio

This paper presents a constant-pressure hydraulic PTO system that can convert stored pressure energy into electrical energy at a stable speed through hydraulic motors and generators. A multi-chamber cylinder can be connected to the main power generation circuit by check valves, and the motor displacement can be controlled by a fuzzy controller to maintain the main power generation circuit under stable pressure. The hydraulic transformer can control the forces applied to the floater. The hydrodynamic parameters of the floater are calculated by AQWA, and the optimal PTO damping of the hydraulic system is analyzed as the target of transformer control. MATLAB/Simulink and AMESim are used to carry out the co-simulation. Three kinds of wave elevation time-series for the specific state are designed for the simulation. In the co-simulation, three approaches are carried out for the simulation including no control strategy, fuzzy control with a fixed transformer ratio, and fuzzy control with a variable transformer ratio. Under the fuzzy control with a fixed transformer ratio, the floater displacement and captured energy do not increase significantly, but the oil pressure fluctuation is very stable, which indicates that the fuzzy controller maintains the stability of the main power circuit. While under fuzzy control with a variable transformer ratio, the power generation is not larger than those under no control strategy or fuzzy control with a fixed transformer ratio, which proves that this hydraulic transformer concept is less efficient.

scholarly journals Fuzzy Control of Cold Storage Refrigeration System with Dynamic Coupling Compensation

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Xiliang Ma ◽  
Ruiqing Mao
Keyword(s):  
Adverse Effects ◽  
Fuzzy Control ◽  
Cold Storage ◽  
Control Strategy ◽  
Control Method ◽  
Fuzzy Controller ◽  
Variable Load ◽  
Variable Degree ◽  
Refrigeration System ◽  
Dynamic Coupling

Cold storage refrigeration systems possess the characteristics of multiple input and output and strong coupling, which brings challenges to the optimize control. To reduce the adverse effects of the coupling and improve the overall control performance of cold storage refrigeration systems, a control strategy with dynamic coupling compensation was studied. First, dynamic model of a cold storage refrigeration system was established based on the requirements of the control system. At the same time, the coupling between the components was studied. Second, to reduce the adverse effects of the coupling, a fuzzy controller with dynamic coupling compensation was designed. As for the fuzzy controller, a self-tuning fuzzy controller was served as the primary controller, and an adaptive neural network was adopted to compensate the dynamic coupling. Finally, the proposed control strategy was employed to the cold storage refrigeration system, and simulations were carried out in the condition of start-up, variable load, and variable degree of superheat, respectively. The simulation results verify the effectiveness of the fuzzy control method with dynamic coupling compensation.

Application Research on H∞ Optimization Control of Permanent Magnet Linear Servo System Based on Adaptive Fuzzy Control Strategy

2013 ◽  
Vol 694-697 ◽  
pp. 2185-2189
Author(s):  
Xiao Ping Zhu ◽  
Xiu Ping Wang ◽  
Chun Yu Qu ◽  
Jun You Zhao
Keyword(s):  
Fuzzy Control ◽  
Control Strategy ◽  
Control Method ◽  
Fuzzy Controller ◽  
External Disturbance ◽  
Adaptive Fuzzy Control ◽  
Servo System ◽  
Robust Controller ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy

In order to against the uncertain disturbance of AC linear servo system, an H mixed sensitivity control method based on adaptive fuzzy control was putted forward in the paper. The controller is comprised of an adaptive fuzzy controller and a H robust controller, the adaptive fuzzy controller is used to approximate this ideal control law, H robust controller is designed for attenuating the approximation errors and the influence of the external disturbance. The experimental results show that this control strategy not only has a strong robustness to uncertainties of the linear system, but also has a good tracking performance, furthermore the control greatly improves the robust tracking precision of the direct drive linear servo system.

A Research on the Fuzzy Control Strategy for Parallel Hybrid Electric Vehicle

2011 ◽  
Vol 121-126 ◽  
pp. 2522-2526
Author(s):  
Ling Cai ◽  
Liang Ge
Keyword(s):  
Fuzzy Control ◽  
Electric Vehicle ◽  
Energy Management ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Fuzzy Controller ◽  
Secondary Development ◽  
Simulation Results ◽  
Hybrid Electric ◽  
Fuzzy Control Strategy

Several kinds of methods of energy management of hybrid electric vehicle (HEV) are analyzed. Based on the design requirement of a certain type of parallel HEV, the fuzzy control strategy of energy management is proposed. ADVISOR2002 is chosen as the simulation platform for secondary development, and the simulation results of the fuzzy control strategy and electric assist control strategy are compared. The simulation results indicate that the adaptive fuzzy controller can obviously improve the performance of HEV fuel economy and emissions.

A Fuzzy Controller for Tentacle Cooperative Robots

2001 ◽  
Author(s):  
Mircea Ivanescu ◽  
Nicu Bizdoaca ◽  
Dorian Cojocaru ◽  
Nirvana Popescu ◽  
Decebal Popescu
Keyword(s):  
Control Strategy ◽  
Fuzzy System ◽  
Fuzzy Controller ◽  
Control Algorithms ◽  
Control Parameters ◽  
Software Simulation ◽  
Contact Points ◽  
Simulation Results ◽  
Hard Contact ◽  
The Stability

Abstract A fuzzy system and the control algorithms are proposed to solve the control multi-chain robotic system formed by tentacle manipulators grasping a commune object with hard contact points. The control system contains two parts: the first component is a conventional controller, which implements a control strategy based on the Lyapunov stability, and the second is an adaptive fuzzy controller which adjusts the control parameters by the output of the first level controller. The stability and robustness is investigated and the fuzzy rules are established The fuzzy controller was developed using Matlab and Simulink software. Simulation results are presented and discussed.

scholarly journals A spintronic memristor crossbar array for fuzzy control with application in the water valves control system

2019 ◽  
Vol 52 (5-6) ◽  
pp. 418-431 ◽  
Author(s):  
Liu Jun ◽  
Xie Shouyong ◽  
Chen Chong ◽  
Xie Dan ◽  
Yang Mingjin
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Real Time ◽  
Control Strategy ◽  
Fuzzy Controller ◽  
Real Time Control ◽  
The Real ◽  
Crossbar Array ◽  
Time Control ◽  
Memristor Crossbar

Fuzzy control, an intelligent control method, is generally employed to deal with complex nonlinear controlled objects that cannot be expressed by accurate mathematical model. Memristor, whose unique advantages are automatic successive memory and nonvolatility, brought new opportunity for solving the key question of fuzzy control. With the design idea of software harden, this paper first constructed membership function in the fuzzy controller based on the unique feature of crossbar array of the spintronic memristor and elaborated the whole construction process. After that, this paper simulated the construction process with MATLAB simulation software, verifying its reasonability and feasibility. Furthermore, a typical fuzzy control water tank system was chosen to explore and discuss the flexibility of spintronic memristor crossbar array in the real-time control system, and the proposed control strategy and the typical fuzzy control strategy were compared. The results revealed that the proposed control strategy was able to attain the effectiveness of the typical fuzzy control system in the real-time control system. This sets light to future research on the implementation of memristor crossbar array in the real-time control system and also promotes the application of fuzzy controller design idea. The problems needed to be solved when implementing memristor crossbar array in the real-time control system were discussed in the final section.

Reliable Robust H∞ Fuzzy Control for Uncertain Nonlinear Systems With Markovian Jumping Actuator Faults

2006 ◽  
Vol 129 (3) ◽  
pp. 252-261 ◽  
Author(s):  
Huai-Ning Wu
Keyword(s):  
Fuzzy Control ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Disturbance Attenuation ◽  
Linear Matrix ◽  
Actuator Faults ◽  
Markovian Jumping ◽  
Stochastically Stable ◽  
The Stability ◽  
Time Systems

This paper is concerned with the design of reliable robust H∞ fuzzy control for uncertain nonlinear continuous-time systems with Markovian jumping actuator faults. The Takagi and Sugeno fuzzy model is employed to represent an uncertain nonlinear system with Markovian jumping actuator faults. First, based on the parallel distributed compensation (PDC) scheme, a sufficient condition such that the closed-loop fuzzy system is robustly stochastically stable and satisfies a prescribed level of H∞-disturbance attenuation is derived. In the derivation process, a stochastic Lyapunov function is used to test the stability and H∞ performance of the system. Then, a new improved linear matrix inequality (LMI) formulation is applied to this condition to alleviate the interrelation between the stochastic Lyapunov matrix and system matrices containing controller variables, which results in a tractable LMI-based condition for the existence of reliable and robust H∞ fuzzy controllers. A suboptimal fuzzy controller is proposed to minimize the level of disturbance attenuation subject to the LMI constraints. Finally, a simulation example is given to illustrate the effectiveness of the proposed method.

scholarly journals Fuzzy Control Strategy Applied to Adjustment of Front Steering Angle of a 4WSD Agricultural Mobile Robot

Lámpsakos ◽  
2012 ◽  
pp. 31
Author(s):  
Henry Borrero-Guerrero ◽  
Rafael Bueno-Sampaio ◽  
Marcelo Becker
Keyword(s):  
Fuzzy Control ◽  
Control Strategy ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Steering System ◽  
Steering Angle ◽  
Lateral Dynamics ◽  
Controller Performance ◽  
Fuzzy Control Strategy ◽  
Real Scale

This paper presents the preliminary studies of the control strategy based in fuzzy logic, projected for the steering system of AGRIBOT project that consist of a wheeled autonomous mobile robotic in real scale endowed with four independent steering and driven wheels (4WSD). In this work we present a preliminary fuzzy controller design applied to front steering angle, using a multivariable plant which incorporates simplified linear model of lateral dynamics of a vehicle whose input are linear combination of rear and front steering angles. The fuzzy control strategy was decided because provides flexible way to deploy with embedded systems. Simulations are used to illustrate the designed controller performance. We use Ackerman geometry to trace front steering angle that allows the vehicle to perform correctly a given maneuver preserving a minimum level of stability and maneuverability. The goal is to establish a relationship between steering input commands and the control commands to the actuators so that it is possible to adjust the attitude of the actuators over the movement axis, as the trajectory change.

Trajectory Tracking Control for a Mobile Robot Using Stochastic Fuzzy Controller

1997 ◽  
Vol 9 (2) ◽  
pp. 160-167
Author(s):  
Jun Tang ◽  
◽  
Keigo Watanabe ◽  
Akira Nomiyama ◽  
◽  
...  
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Mobile Robot ◽  
Fuzzy Controller ◽  
Control Object ◽  
Circular Path ◽  
Unknown Parameters ◽  
Trajectory Tracking Control ◽  
Practical Applications ◽  
The Stability

This paper presents a new design for a fuzzy controller, called ""stochastic fuzzy control."" It describes the application controlling a mobile robot driven by two independent wheels. Using this scheme, the fuzzy control system provides an optimal stochastic control strategy that ensures the stability of the control system. Two design methods are considered: one assumes that the control object is completely known, and the other assumes that the control object includes unknown parameters. We design the straight line and circular path reference trajectories in accordance with the practical applications for the mobile robot, in which three patterns of speed are adopted. The effectiveness of the proposed method is demonstrated by a series of practical tests using our experimental mobile robot.

Application of Fuzzy Control Technology in a Sonar-Based Obstacle Avoidance Intelligent Wheelchair

2013 ◽  
Vol 321-324 ◽  
pp. 2004-2008 ◽  
Author(s):  
Ting Su ◽  
Guo Hua Cao ◽  
Ji Hua Hu
Keyword(s):  
Fuzzy Control ◽  
Obstacle Avoidance ◽  
Control Strategy ◽  
Fuzzy Controller ◽  
Control Technology ◽  
Application System ◽  
Intelligent Wheelchair ◽  
System Use ◽  
Measured Distance ◽  
Fuzzy Control Strategy

The paper presents a kind of application system combining fuzzy control technology and ultrasonic obstacle avoidance technology for the intelligent wheelchair (iwheelchair). The system use the ultrasonic measured-distance as the input signal and the output signal is the speed of the iwheelchair to avoid obstacle. The fuzzy controller is designed in Matlab platform and simulated according to the obtained fuzzy control strategy. The fuzzy control technology has been applied successfully in ultrasound obstacle avoidance system for the intelligent wheelchair.

scholarly journals PERFORMANCE ANALYSIS FUZZY-PID VERSUS FUZZY FOR QUADCOPTER ALTITUDE LOCK SYSTEM

2015 ◽  
Vol 77 (22) ◽  
Author(s):  
Hendi Wicaksono ◽  
Yohanes Gunawan ◽  
Arbil Yodinata ◽  
Leonardie Leonardie
Keyword(s):  
Performance Analysis ◽  
Fuzzy Control ◽  
Control Method ◽  
Fuzzy Controller ◽  
Sensor Data ◽  
Fuzzy Pid ◽  
Motor Speed ◽  
Fuzzy Pid Control ◽  
Comparative Performance ◽  
The Stability

Mostly quadcopter has a flight controller to receive signal from remote control to control four brushless motor speed. In this paper, the researchers introduced a new control method to make quadcopter altitude lock system using Fuzzy-PID and perform a comparative  performance analysis between the Fuzzy controller and the new Fuzzy-PID controller. Fuzzy controller has ability to solve uncertainty within the system, by incorporating with altitude sensor data. On the other hand, Fuzzy-PID has the ability to gain the target level with Kp, Ki, Kd values controlled. In this paper the researchers present an analysis to compare the control method between Fuzzy and Fuzzy-PID with regards to the stability altitude lock system. The stability of the altitude lock system can be measured by how small the oscillations occurred. Fuzzy control has shown to produce better result than Fuzzy-PID control. Fuzzy control has 14 cm as its average oscillation, while Fuzzy-PID recorded 24 cm as its average oscillation.  

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