A dynamic inverse control law for hypersonic vehicles based on fuzzy logic

2014 ◽  
Author(s):  
Wang Jian ◽  
Yao Li
Keyword(s):  
Fuzzy Logic ◽  
Control Law ◽  
Hypersonic Vehicles ◽  
Inverse Control ◽  
Dynamic Inverse

Comparison of a Fuzzy Logic Controller With a P + D Control Law

1989 ◽  
Vol 111 (2) ◽  
pp. 128-137 ◽  
Author(s):  
S. Daley ◽  
K. F. Gill
Keyword(s):  
Fuzzy Logic ◽  
Attitude Control ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Good Control ◽  
Control Law ◽  
Dynamic Coupling ◽  
Process Knowledge ◽  
Logic Control ◽  
Limited Process

A study is described that compares the performance of a self-organizing fuzzy logic control law (SOC) with that of the more traditional P + D algorithm. The multivariate problem used for the investigation is the attitude control of a flexible satellite that has significant dynamic coupling of the axes. It is demonstrated that the SOC can provide good control, requires limited process knowledge and compares favorably with the P + D algorithm.

Parameter identification for load frequency control using fuzzy FOPID in power system

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ram Kumar ◽  
Afzal Sikander
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Parameter Identification ◽  
Fractional Order ◽  
Optimization Technique ◽  
Load Frequency Control ◽  
Control Law ◽  
Content Type ◽  
Load Frequency ◽  
Frequency Controller

Purpose This paper aims to suggest the parameter identification of load frequency controller in power system. Design/methodology/approach The suggested control approach is established using fuzzy logic to design a fractional order load frequency controller. A new suitable control law is developed using fuzzy logic, and based on this developed control law, the unknown parameters of the fractional order proportional integral derivative (FOPID) controller are derived using an optimization technique, which is being used by minimizing the integral square error. In addition, to confirm the effectiveness of the proposed control design approach, numerous simulation tests were carried out on an actual single-area power system. Findings The obtained results reveal the superiority of the suggested controller as compared to the recently developed controllers with regard to time response specifications and quantifiable indicators. Additionally, the potential of the suggested controller is also observed by improving the load disturbance rejections under plant parametric uncertainty. Originality/value To the best of the authors’ knowledge, the work is not published anywhere else.

scholarly journals Deformation Reconstruction and High-Precision Attitude Control of a Launch Vehicle Based on Strain Measurements

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Liang Zhuang ◽  
Zhang Yulin
Keyword(s):  
High Precision ◽  
Attitude Control ◽  
Control Method ◽  
Launch Vehicles ◽  
Bending Vibration ◽  
Inverse Control ◽  
Deformation Parameters ◽  
Control Framework ◽  
Fbg Sensors ◽  
Dynamic Inverse

The development of launch vehicles has led to higher slenderness ratios and higher structural efficiencies, and the traditional control methods have difficulty in meeting high-quality control requirements. In this paper, an incremental dynamic inversion control method based on deformation reconstruction is proposed to achieve high-precision attitude control of slender launch vehicles. First, the deformation parameters of a flexible rocket are obtained via fiber Bragg grating (FBG) sensors. The deformation and attitude information is introduced into the incremental dynamic inverse control loop, and an attitude control framework that can alleviate bending vibration and deformation is established. The simulation results showed that the proposed method could accurately reconstruct the shapes of flexible launch vehicles with severe vibration and deformation, which could improve the accuracy and stability of attitude control.

A Nonlinear Fuzzy Logic Controller Developed for an Autonomous Surface Boat

2005 ◽  
Author(s):  
Thomas A. Bean ◽  
Akira Okamoto ◽  
John R. Canning ◽  
Dean B. Edwards
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Optimization Method ◽  
Operating Point ◽  
Linear Feedback ◽  
Control Law ◽  
Linear Feedback Control ◽  
Linear Controller ◽  
Optimal Linear ◽  
Optimal Set

This paper presents an optimized nonlinear fuzzy logic controller designed for an autonomous surface craft and describes the process by which it was found. The nonlinear fuzzy logic controller described herein was developed to maintain the linear feedback control of an optimal set of controller gains when the state is near the operating point. The simplex optimization method was utilized to find the optimal fuzzy logic parameters that define the shape of the control law away from the normal operating point. The resultant controller showed approximately a 20% improvement over the optimal linear controller.

scholarly journals Robust ℋ∞-Fuzzy Logic Control for Enhanced Tracking Performance of a Wheeled Mobile Robot in the Presence of Uncertain Nonlinear Perturbations

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3673 ◽  
Author(s):  
Nur Ahmad
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Wheeled Mobile Robot ◽  
Tracking Performance ◽  
Model Parameters ◽  
Control Law ◽  
System Modelling ◽  
Nonlinear Perturbations ◽  
Model Errors ◽  
Dc Motors

Motion control involving DC motors requires a closed-loop system with a suitable compensator if tracking performance with high precision is desired. In the case where structural model errors of the motors are more dominating than the effects from noise disturbances, accurate system modelling will be a considerable aid in synthesizing the compensator. The focus of this paper is on enhancing the tracking performance of a wheeled mobile robot (WMR), which is driven by two DC motors that are subject to model parametric uncertainties and uncertain deadzones. For the system at hand, the uncertain nonlinear perturbations are greatly induced by the time-varying power supply, followed by behaviour of motion and speed. In this work, the system is firstly modelled, where correlations between the model parameters and different input datasets as well as voltage supply are obtained via polynomial regressions. A robust H ∞ -fuzzy logic approach is then proposed to treat the issues due to the aforementioned perturbations. Via the proposed strategy, the H ∞ controller and the fuzzy logic (FL) compensator work in tandem to ensure the control law is robust against the model uncertainties. The proposed technique was validated via several real-time experiments, which showed that the speed and path tracking performance can be considerably enhanced when compared with the results via the H ∞ controller alone, and the H ∞ with the FL compensator, but without the presence of the robust control law.

Sign in / Sign up

Export Citation Format

Share Document