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.

scholarly journals Neural Network Control System of UAV Altitude Dynamics and Its Comparison with the PID Control System

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Jemie Muliadi ◽  
Benyamin Kusumoputro
Keyword(s):  
Control System ◽  
Pid Control ◽  
Attitude Control ◽  
Control Method ◽  
Comparative Method ◽  
Linear Method ◽  
Network Control ◽  
Analysis Tool ◽  
Inverse Control ◽  
Pid Tuning

This article proposes a comparative method to assess the performance of artificial neural network’s direct inverse control (DIC-ANN) with the PID control system. The comparison served as an analysis tool to assess the advantages of DIC-ANN over conventional control method for a UAV attitude controller. The development of ANN method for UAV control purposes arises due to the limitations of the conventional control method, which is the mathematical based model, involving complex expression, and most of them are difficult to be solved directly into analytic solution. Although the linearization simplified the solving process for such mathematical based model, omitting the nonlinear and the coupling terms is unsuitable for the dynamics of the multirotor vehicle. Thus, the DIC-ANN perform learning mechanism to overcome the limitation of PID tuning. Therefore, the proposed comparative method is developed to obtain conclusive results of DIC-ANN advantages over the linear method in UAV attitude control. Better achievement in the altitude dynamics was attained by the DIC-ANN compared to PID control method.

scholarly journals Dynamic modeling and control method of a new concept wing-disk aircraft

2018 ◽  
Vol 189 ◽  
pp. 03015
Author(s):  
Da Hong ◽  
Jihong Zhu
Keyword(s):  
Flight Control ◽  
Control Method ◽  
Poor Performance ◽  
Previous Method ◽  
Modeling And Control ◽  
Inverse Control ◽  
Wing Disk ◽  
Integral Element ◽  
Dynamic Inverse ◽  
And Control

The research aimed at a new layout wing-disk solar aircraft concept with several wings around the disc fuselage, select coordinates and variables adaptively for the new dynamic subject, and establish dynamic model, using blade element momentum theory and CFD value for correction. Design the flight control strategy and controller constraint relations, put forward the method of control allocation and manipulation, and use nonlinear dynamic inversion control method aimed at the transverse and longitudinal coupling, serious nonlinear characteristics, and adds integral element as a robust dynamic inverse control to deal with the poor performance of previous method, and simulate to validate the control design.

Coordinated optimization control of shield machine based on dynamic fuzzy neural network direct inverse control

2020 ◽  
pp. 014233122098027
Author(s):  
Xuanyu Liu ◽  
Wentao Wang ◽  
Yudong Wang ◽  
Cheng Shao ◽  
Qiumei Cong
Keyword(s):  
Fuzzy Neural Network ◽  
Control Method ◽  
Earth Pressure ◽  
Screw Conveyor ◽  
Inverse Control ◽  
The Earth ◽  
Coordinated Optimization ◽  
Optimization Control ◽  
Fuzzy Neural ◽  
Shield Machine

During shield machine tunneling, the earth pressure in the sealed cabin must be kept balanced to ensure construction safety. As there is a strong nonlinear coupling relationship among the tunneling parameters, it is difficult to control the balance between the amount of soil entered and the amount discharged in the sealed cabin. So, the control effect of excavation face stability is poor. For this purpose, a coordinated optimization control method of shield machine based on dynamic fuzzy neural network (D-FNN) direct inverse control is proposed. The cutter head torque, advance speed, thrust, screw conveyor speed and earth pressure difference in the sealed cabin are selected as inputs, and the D-FNN control model of the control parameters is established, whose output are screw conveyor speed and advance speed at the next moment. The error reduction rate method is introduced to trim and identify the network structure to optimize the control model. On this basis, an optimal control system for earth pressure balance (EPB) of shield machine is established based on the direct inverse control method. The simulation results show that the method can optimize the control parameters coordinately according to the changes of the construction environment, effectively reduce the earth pressure fluctuations during shield tunneling, and can better control the stability of the excavation surface.

scholarly journals Design and validation of an MPC controller for CMG-based testbed

2021 ◽  
Author(s):  
Matteo Facchino ◽  
Atsushi Totsuka ◽  
Elisa Capello ◽  
Satoshi Satoh ◽  
Giorgio Guglieri ◽  
...  
Keyword(s):  
Predictive Control ◽  
Attitude Control ◽  
High Speed ◽  
Control Method ◽  
Input Constraints ◽  
Virtual Reference ◽  
Control Moment ◽  
Pyramidal Configuration ◽  
Actuation Systems ◽  
Constraints Satisfaction

AbstractIn the last years, Control Moment Gyros (CMGs) are widely used for high-speed attitude control, since they are able to generate larger torque compared to “classical” actuation systems, such as Reaction Wheels . This paper describes the attitude control problem of a spacecraft, using a Model Predictive Control method. The features of the considered linear MPC are: (i) a virtual reference, to guarantee input constraints satisfaction, and (ii) an integrator state as a servo compensator, to reduce the steady-state error. Moreover, the real-time implementability is investigated using an experimental testbed with four CMGs in pyramidal configuration, where the capability of attitude control and the optimization solver for embedded systems are focused on. The effectiveness and the performance of the control system are shown in both simulations and experiments.

Decoupling Control for Bearingless Synchronous Reluctance Motor Based on Neural Networks Inverse

2012 ◽  
Vol 150 ◽  
pp. 30-35
Author(s):  
Ze Bin Yang ◽  
Huang Qiu Zhu ◽  
Xiao Dong Sun ◽  
Tao Zhang
Keyword(s):  
Neural Networks ◽  
Control Method ◽  
Decoupling Control ◽  
Performance Simulation ◽  
Inverse Control ◽  
Linear Control Theory ◽  
Synchronous Reluctance Motor ◽  
Reluctance Motor ◽  
Static Performance ◽  
Simulation And Experiment

A novel decoupling control method based on neural networks inverse system is presented in this paper for a bearingless synchronous reluctance motor (BSRM) possessing the characteristics of multi-input-multi-output, nonlinearity, and strong coupling. The dynamic mathematical models are built, which are verified to be invertible. A controller based on neural network inverse is designed, which decouples the original nonlinear system to two linear position subsystems and an angular velocity subsystem. Furthermore, the linear control theory is applied to closed-loop synthesis to meet the desired performance. Simulation and experiment results show that the presented neural networks inverse control strategy can realize the dynamic decoupling of BSRM, and that the control system has fine dynamic and static performance.

Design of a High-Precision Flyback Constant Voltage AC–DC Converter

2017 ◽  
Vol 26 (11) ◽  
pp. 1750175
Author(s):  
Changyuan Chang ◽  
Chao Hong ◽  
Yang Xu ◽  
Hailong Sun ◽  
Yao Chen
Keyword(s):  
High Precision ◽  
Output Voltage ◽  
Control Method ◽  
Switching Frequency ◽  
Constant Voltage ◽  
Light Load ◽  
Wave Generator ◽  
Load Regulation ◽  
High Output

A constant voltage AC–DC converter based on the digital assistant technology is proposed in this paper, which has the advantage of high output precision. In this paper, a novel digital exponential wave generator is adopted in Constant Voltage (CV) mode to replace the normal triangle waveform to obtain a wider range of switching frequency, increasing the accuracy of output voltage under light load. The control chip is implemented based on NEC 1[Formula: see text][Formula: see text]m 5[Formula: see text]V/40[Formula: see text]V HVCMOS process, and a 5[Formula: see text]V/1.2[Formula: see text]A prototype has been built to verify the proposed control method. In PFM mode the deviation of output voltage is within [Formula: see text]% and the load regulation is [Formula: see text]%. Meanwhile, when the load jumps from light to heavy, the minimum output voltage could be maintained above 4.16[Formula: see text]V.

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