scholarly journals Center of Pressure Feedback for Controlling the Walking Stability Bipedal Robots using Fuzzy Logic Controller

Author(s):  
Afrizal Mayub ◽  
Fahmizal Fahmizal

This paper presents a sensor-based stability walk for bipedal robots by using force sensitive resistor (FSR) sensor. To perform walk stability on uneven terrain conditions, FSR sensor is used as feedbacks to evaluate the stability of bipedal robot instead of the center of pressure (CoP). In this work, CoP that was generated from four FSR sensors placed on each foot-pad is used to evaluate the walking stability. The robot CoP position provided an indication of walk stability. The CoP position information was further evaluated with a fuzzy logic controller (FLC) to generate appropriate offset angles to be applied to meet a stable situation. Moreover, in this paper designed a FLC through CoP region's stability and stable compliance control are introduced. Finally, the performances of the proposed methods were verified with 18-degrees of freedom (DOF) kid-size bipedal robot.<br /><br />

Author(s):  
Habibullah Salim ◽  
Irma Husnaini ◽  
Asnil Asnil

This research aims to make buck converter prototype for PLTS system by using fuzzy logic controller. Buck converter is required in the PLTS system if the required unidirectional voltage is smaller than the output voltage of the solar cell. Buck converter used to convert 24 Volt dc voltage to 12 Volt dc with 60 watt capability. While fuzzy logic controller is used to improve buck converter performance based on pulse generation technique for switching. The application of fuzzy logic method is expected to improve the performance of the system by maintaining the stability of buck converter output voltage of 12 volts and reduce the output ripple value. Atmega8535 microcontroller is used to generate PWM pulses for switching on power circuits. The results obtained from the test using a 100 Ohm 5 Watt load obtained the buck converter output voltage of 12.4 Volt.


2004 ◽  
Vol 10 (4) ◽  
pp. 493-506 ◽  
Author(s):  
A. Jnifene ◽  
W Andrews

This paper is concerned with the design and implementation of a fuzzy logic controller (FLC) to control the end-point vibration in a single flexible beam mounted on a two-degrees-of-freedom platform. The angular position of the hub and the signal from a strain gage mounted on the beam are used as the two inputs to the FLC. In order to add more damping, the strain gage signal is combined with the hub angular velocity represented by the output of a tachometer attached to the motor shaft. We discuss how to build the rule base for the flexible beam based on the relation between the angular displacement of the hub and the end-point deflection, as well as the effect of different scaling gains on the performance of the FLC. We present several experimental results showing the effectiveness of the FLC in reducing the end-point vibration of the flexible beam.


Author(s):  
Mustefa Jibril

Accurate and precise trajectory tracking is crucial for a quadrotor to operate in disturbed environments. This paper presents a novel tracking hybrid controller for a quadrotor UAV that combines the Adaptive and Fuzzy logic controller. The Adaptive fuzzy controller is implemented to govern the behavior of two degrees of freedom quadrotor UAV. The proposed controller allows controlling the movement of UAVs to track a given trajectory in a 2D vertical plane. The Fuzzy Logic system provides an automatic adjustment of the Adaptive parameters to reduce tracking errors and improve the quality of the controller. The results showed perfect behavior for the control law to control a quadrotor trajectory tracking task. To show the effectiveness of the intelligent controller, simulation results are given to confirm the advantages of the proposed control method, compared with Fuzzy and Proportional integral derivative (PID) control methods.


2021 ◽  
pp. 22-30
Author(s):  
Kahramon R. ALLAEV ◽  
◽  
Tokhir F. MAKHMUDOV ◽  

Power systems are large non-linear systems that are often subject to low frequency electromechanical oscillations with a frequency of 0.5–2.5 Hz. Power system stabilizers (PSS) are commonly used as effective and economically efficient means to dampen electromechanical oscillations of generators and increase the stability of power systems. PSS can increase the power transmission stability limits by adding a stabilizing signal through the channels of the automatic excitation control system. The article presents the results of training a neural network based on which a fuzzy logic PSS is obtained for increasing the stability of electric power systems. The synchronous generator rotor speed deviation and acceleration were taken as input data for the fuzzy logic controller. These variables have a significant effect on damping the rotor's electromechanical oscillations. The characteristics of the power system equipped with the proposed fuzzy logic based PSS are compared with its characteristics with a PSS with non-optimized parameters and without a PSS.


Author(s):  
A.S Emam

This study details an efficient fuzzy logic controller (FLC) to improve the performance of active automotive suspension system. A comparison between passive and FLC active suspensions is performed. A mathematical model of automotive active suspension has six degrees of freedom and two input forces generated by two separate actuators are solved using Matlab Simulink. In order to evaluate the effectiveness of the proposed controller under random road disturbance, several performance criteria are assessed based on the dynamic response of the half automotive suspension system. Simulation results of the active suspension system based on the fuzzy logic clearly have been provided to illustrate the effectiveness of the FLC under different road conditions and confirmed that fuzzy logic is very effective for enhancing ride comfort and stability of the vehicle.


Author(s):  
Siavash Rezazadeh ◽  
Robert D. Gregg

Although dynamic walking methods have had notable successes in control of bipedal robots in the recent years, still most of the humanoid robots rely on quasi-static Zero Moment Point controllers. This work is an attempt to design a highly stable controller for dynamic walking of a human-like model which can be used both for control of humanoid robots and prosthetic legs. The method is based on using time-based trajectories that can induce a highly stable limit cycle to the bipedal robot. The time-based nature of the controller motivates its use to entrain a model of an amputee walking, which can potentially lead to a better coordination of the interaction between the prosthesis and the human. The simulations demonstrate the stability of the controller and its robustness against external perturbations.


2018 ◽  
Author(s):  
Asnil ◽  
Habibullah ◽  
Irma Husnaini

This research aims to make buck converter prototype for PLTS system by using fuzzy logic controller. Buck converter is required in the PLTS system if the required unidirectional voltage is smaller than the output voltage of the solar cell. Buck converter used to convert 24 Volt dc voltage to 12 Volt dc with 60 watt capability. While fuzzy logic controller is used to improve buck converter performance based on pulse generation technique for switching. The application of fuzzy logic method is expected to improve the performance of the system by maintaining the stability of buck converter output voltage of 12 volts and reduce the output ripple value. Atmega8535 microcontroller is used to generate PWM pulses for switching on power circuits.


2019 ◽  
Vol 8 (2) ◽  
pp. 5548-5554

By the coordination of the superconducting fault current limiter (SFCL), superconducting magnetic energy storage (SMES) and distributed generation (DG) units, the stability of the microgrid is increased under short circuit fault conditions. And by this coordination control, the microgrid is smoothly separated from the main network under severe fault and attains a fault ride through (FRT) operation under minor fault. In this paper, to overcome the drawbacks of the PI controller a fuzzy logic controller (FLC) is used in the controller of the SFCL. This proposed method is carried out in a MATLAB/Simulink. The results show the achievement of a better control strategy.


2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Manuel Braz César ◽  
Rui Carneiro Barros

Abstract In this paper, we report on the development of a neuro-fuzzy controller for magnetorheological dampers using an Adaptive Neuro-Fuzzy Inference System or ANFIS. Fuzzy logic based controllers are capable to deal with non-linear or uncertain systems, which make them particularly well suited for civil engineering applications. The main objective is to develop a semi-active control system with a MR damper to reduce the response of a three degrees-of-freedom (DOFs) building structure. The control system is designed using ANFIS to optimize the fuzzy inference rule of a simple fuzzy logic controller. The results show that the proposed semi-active neuro-fuzzy based controller is effective in reducing the response of structural system.


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