scholarly journals The Investigation on L 1 Adaptive Control of the Tilt-Rotor Aircraft

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Quanlong Chen ◽  
Shanyong Zhao ◽  
Ke Lu ◽  
Senkui Lu ◽  
Chunsheng Liu ◽  
...  
Keyword(s):  
Control System ◽  
Adaptive Design ◽  
Reference Signal ◽  
Engineering Application ◽  
Adaptive Controller ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Tilt Rotor ◽  
Conversion Mode ◽  
Flight Dynamics Model

Considering the uncertainty of the flight dynamics model of the tilt-rotor aircraft in different flight modes, an L 1 adaptive controller for full flight modes control system of tilt-rotor aircraft is designed. Taking advantage of the separation of robustness and adaptive design of the L 1 adaptive controller, adaptive gain, and low-pass filter are designed to achieve the desired control performance and meet the requirements of flight quality. The simulations of XV-15 tilt-rotor aircraft in helicopter mode and airplane mode are carried out. Then, the simulation of conversion mode is further carried out. The results show that the tilt-rotor aircraft can track the reference signal well under the L 1 control system. In addition, the changes of states as well as controls in conversion mode flight are quite smooth which is very meaningful for engineering application.

PMSM Control System Based on a Improved Sliding Mode Observer

2013 ◽  
Vol 307 ◽  
pp. 27-30 ◽  
Author(s):  
Yu Feng Zhang ◽  
Sheng Jin Li ◽  
Yong Zhou ◽  
Qi Xun Zhou
Keyword(s):  
Control System ◽  
Vector Control ◽  
Sliding Mode ◽  
Interpolation Method ◽  
Linear Interpolation ◽  
Sliding Mode Observer ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Field Oriented Vector Control ◽  
Vector Control System

In order to improve the performance of sensorless PMSM control system, an improved sliding mode observer (SMO) is proposed in this paper. To decrease the vibration of SMO, a variable switching gain which changes according to the winding currentn is adopted. To improve the estimated value of rotor position, a extra low pass filter (LPF) is employed and the linear interpolation method is used to calculate compensation value of the phase delay caused by LPF. To verify the performance of proposed SMO, a sensorless field oriented vector control system of PMSM is designed. At last, the performance of the improved SMO and the sensorless PMSM vector control system are verified by experimental results.

scholarly journals Neural NetworkL1Adaptive Control of MIMO Systems with Nonlinear Uncertainty

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Hong-tao Zhen ◽  
Xiao-hui Qi ◽  
Jie Li ◽  
Qing-min Tian
Keyword(s):  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Adaptive Controller ◽  
Rbf Neural Networks ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Input Multiple Output ◽  
Low Pass ◽  
Nonlinear Uncertainties

An indirect adaptive controller is developed for a class of multiple-input multiple-output (MIMO) nonlinear systems with unknown uncertainties. This control system is comprised of anL1adaptive controller and an auxiliary neural network (NN) compensation controller. TheL1adaptive controller has guaranteed transient response in addition to stable tracking. In this architecture, a low-pass filter is adopted to guarantee fast adaptive rate without generating high-frequency oscillations in control signals. The auxiliary compensation controller is designed to approximate the unknown nonlinear functions by MIMO RBF neural networks to suppress the influence of uncertainties. NN weights are tuned on-line with no prior training and the project operator ensures the weights bounded. The global stability of the closed-system is derived based on the Lyapunov function. Numerical simulations of an MIMO system coupled with nonlinear uncertainties are used to illustrate the practical potential of our theoretical results.

scholarly journals An Internal Model-Based PID Control for Smart Shot Peening Operation

2021 ◽  
pp. 15-33
Author(s):  
V. B. Nguyen ◽  
T. Ba ◽  
A. Teo ◽  
K. Ahluwalia ◽  
A. Aramcharoen ◽  
...  
Keyword(s):  
Control System ◽  
Pid Control ◽  
Shot Peening ◽  
System Development ◽  
Pressure Sensors ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Model Based ◽  
Extreme Gradient Boosting ◽  
Site Control

Current control systems for the shot peening operation merely rely on old technologies, which often require repetitive processes to obtain pre-validated Almen systems to guide industrial productions. These designs for the manufacturing paradigm are not efficient for complicated workflows in modern manufacturing operation. Thus, in this study, we propose a practical model-based control system to address the issues; especially for a smarter and automated shot peening machine. In particular, the closed-loop control system development utilizes a model-based proportional-integral-derivative (PID) control technology and extreme gradient boosting (XGBOOST) machine learning algorithm. The control system includes an internal process model, a proxy model, a model-based PID controller, and pressure sensors with a low-pass filter for feedback control. The developed control system is integrated into a physical shot peening machine for on-site control validation and demonstration. In both in-silico and on-site control demonstrations, the obtained control performance is stable, robust, and reliable for different operational conditions. The measurement intensities are very close to targeted setting intensities. All the differences are smaller than the industrial threshold of (±0.01 mmA). It implies that the control system can use in industrial peening operations without the need for Almen system development for operational guidance. In other words, the control system can significantly reduce the total cost of the actual production by eliminating the cost, time, and labor of the iterative trials to build the Almen system.

Application of IMC-PID in the Hydraulic Headbox Total Pressure Control

2012 ◽  
Vol 462 ◽  
pp. 789-795
Author(s):  
Wei Tang ◽  
Xu Zhong Niu ◽  
Wen Juan Shan
Keyword(s):  
Control System ◽  
Time Constant ◽  
Total Pressure ◽  
Pressure Control ◽  
Internal Model Control ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Model Control ◽  
Low Pass ◽  
Pressure Control System

It is very difficult to obtain perfect performance to apply the conventional PID (Proportional-Integral-Derivative) controller, because hydraulic headbox needs high precision total pressure control. Transfer function of total pressure control system was identified by using the direct identification method which is based on the least square method for the first-order plus delay time model. Then combined with IMC (Internal-Model-control) –PID method, an IMC-PID controller was designed, which is simple and only needed to adjust one parameter-the time constant of low pass filter. Acceptable performance can also be obtained by tuning time constant of the low pass filter when the model doesn't match with the real process. The algorithm was applied to total pressure control system of hydraulic headbox. Simulation and practical application show that, IMC-PID is of strong robustness and good dynamic characteristics. Finally, the control system is implemented by S7-300 PLC.

scholarly journals Sliding Mode Control for Bearingless Induction Motor Based on a Novel Load Torque Observer

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Zebin Yang ◽  
Ling Wan ◽  
Xiaodong Sun ◽  
Lin Chen ◽  
Zheng Chen
Keyword(s):  
Control System ◽  
Induction Motor ◽  
Sliding Mode ◽  
Rotational Inertia ◽  
Observation Error ◽  
Load Torque ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass ◽  
Adverse Influence

For the problem of low control performance of Bearingless Induction Motor (BIM) control system in the presence of large load disturbance, a novel load torque sliding mode observer is proposed on the basis of establishing sliding mode speed control system. The load observer chooses the speed and load torque of the BIM control system as the observed objects, uses the speed error to design the integral sliding mode surface, and adds the low-pass filter to reduce the torque observation error. Meanwhile, the output of the load torque is used as the feedforward compensation for the control system, which can provide the required current for load changes and reduce the adverse influence of disturbance on system performance. Besides, considering that the load changes lead to the varying rotational inertia, the integral identification method is adopted to identify the rotational inertia of BIM, and the rotational inertia can be updated to the load observer in real time. The simulation and experiment results all show that the proposed method can track load torque accurately, improve the ability to resist disturbances, and ameliorate the operation quality of BIM control system. The chattering of sliding mode also is suppressed effectively.

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