Data Driven Model-Free Adaptive Control Method for Quadrotor Trajectory Tracking Based on Improved Sliding Mode Algorithm

2020 ◽  
Author(s):  
Dongdong Yuan ◽  
Yankai Wang
Keyword(s):  
Adaptive Control ◽  
Trajectory Tracking ◽  
Control Method ◽  
Sliding Mode ◽  
Data Driven ◽  
Model Free

scholarly journals Data Driven Model-Free Adaptive Control Method for Quadrotor Formation Trajectory Tracking Based on RISE and ISMC Algorithm

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1289
Author(s):  
Dongdong Yuan ◽  
Yankai Wang
Keyword(s):  
Adaptive Control ◽  
Sliding Mode Control ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Control Method ◽  
Sliding Mode ◽  
Data Driven ◽  
Trajectory Tracking Control ◽  
Mode Control ◽  
Model Free

In order to solve the problems of complex dynamic modeling and parameters identification of quadrotor formation cooperative trajectory tracking control, this paper proposes a data-driven model-free adaptive control method for quadrotor formation based on robust integral of the signum of the error (RISE) and improved sliding mode control (ISMC). The leader-follower strategy is adopted, and the leader realizes trajectory tracking control. A novel asymptotic tracking data-driven controller of quadrotor is used to control the system using the RISE method. It is divided into two parts: The inner loop is for attitude control and the outer loop for position control. Both use the RISE method in the loop to eliminate interference and this method only uses the input and output data of the unmanned aerial vehicle(UAV) system and does not rely on any dynamics and kinematics model of the UAV. The followers realize formation cooperative control, introducing adaptive update law and saturation function to improve sliding mode control (SMC), and it eliminates the general SMC algorithm controller design dependence on the mathematical model of the UAV and has the chattering problem. Then, the stability of the system is proved by the Lyapunov method, and the effectiveness of the algorithm and the feasibility of the scheme are verified by numerical simulation. The experimental results show that the designed data-driven model-free adaptive control method for the quadrotor formation is effective and can effectively realize the coordinated formation trajectory tracking control of the quadrotor. At the same time, the design of the controller does not depend on the UAV kinematics and dynamics model, and it has high control accuracy, stability, and robustness.

scholarly journals Trajectory Tracking Control for Parafoil Systems Based on the Model-Free Adaptive Control Method

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 152620-152636
Author(s):  
Linggong Zhao ◽  
Weiliang He ◽  
Feikai Lv ◽  
Wang Xiaoguang
Keyword(s):  
Adaptive Control ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Control Method ◽  
Trajectory Tracking Control ◽  
Model Free

scholarly journals Model-free-adaptive-based data-driven method for three-axis Gimbal control

2020 ◽  
Vol 53 (7-8) ◽  
pp. 1512-1517
Author(s):  
Wei Wang ◽  
Javed Masood Rana
Keyword(s):  
Adaptive Control ◽  
Position Control ◽  
Control Method ◽  
Sliding Mode ◽  
Computational Time ◽  
Measurement Unit ◽  
Brushless Dc ◽  
Model Free ◽  
Three Phase ◽  
The Given

This study uses a three-axis Gimbal model to inertially stabilize a platform that can be used to feed smooth images from a camera. In this article, three-axis Gimbal performance analysis is presented. An inertial measurement unit responds to movement and a three-phase brushless DC motor with 14 poles and 12 coils is used to rule out vibrations and movement from the surroundings. The controller combines sliding-mode control and model-free-adaptive control to design a novel control method based on data, which can decrease the computational time and difficulty of a nonlinear system. Simulations on MATLAB prove the efficiency of the given method. The simulation results validate that the designed controller has improved position control than the traditional proportional integral derivative, model-free-adaptive control, and model-free-learning-adaptive control.

Anti-noise model-free adaptive control and its application in the circulating fluidized bed boiler

2020 ◽  
pp. 095965182097937
Author(s):  
Na Dong ◽  
Wenjin Lv ◽  
Shuo Zhu ◽  
Donghui Li
Keyword(s):  
Adaptive Control ◽  
Complete Convergence ◽  
Circulating Fluidized Bed ◽  
Control Method ◽  
Noise Model ◽  
Good Resistance ◽  
Industrial Systems ◽  
Noise Interference ◽  
Model Free ◽  
Tracking Differentiator

Model-free adaptive control has been developed greatly since it was proposed. Up to now, model-free adaptive control theory has become mature and tends to be an effective solution for complex unmodeled industrial systems. In practical industrial processes, most control systems are inevitably accompanied by noise that will result in indelible error and may further cause inaccurate feedback to the output. In order to solve this kind of problem with model-free technique, this article incorporates an improved tracking differentiator into model-free adaptive control. After that, the anti-noise model-free adaptive control method with complete convergence analysis is proposed. Meanwhile, numerical simulation proves that the improved control method can quickly track a given signal with good resistance to noise interference. Finally, the effectiveness and practicability of the proposed algorithm are verified by experiments through the control of drum water level of circulating fluidized.

Data-driven tracking consensus for a class of unknown nonlinear multi-agent systems

2021 ◽  
pp. 107754632110340
Author(s):  
Jia Wu ◽  
Ning Liu ◽  
Wenyan Tang
Keyword(s):  
Control Method ◽  
Sufficient Conditions ◽  
Data Driven ◽  
The Novel ◽  
Multi Agent Systems ◽  
Tracking Errors ◽  
Agent Systems ◽  
Model Free ◽  
Strongly Connected ◽  
Multi Agent

This study investigates the tracking consensus problem for a class of unknown nonlinear multi-agent systems A novel data-driven protocol for this problem is proposed by using the model-free adaptive control method To obtain faster convergence speed, one-step-ahead desired signal is introduced to construct the novel protocol Here, switching communication topology is considered, which is not required to be strongly connected all the time Through rigorous analysis, sufficient conditions are given to guarantee that the tracking errors of all agents are convergent under the novel protocol Examples are given to validate the effectiveness of results derived in this article

scholarly journals Improved Model-Free Adaptive Sliding-Mode-Constrained Control for Linear Induction Motor considering End Effects

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Xiaoqi Song ◽  
Dezhi Xu ◽  
Weilin Yang ◽  
Yan Xia ◽  
Bin Jiang
Keyword(s):  
Control Method ◽  
Sliding Mode ◽  
Dynamic Performance ◽  
Research Field ◽  
Constrained Control ◽  
End Effects ◽  
Linear Induction ◽  
Adaptive Sliding Mode ◽  
Model Free ◽  
Improved Model

As a kind of special motors, linear induction motors (LIM) have been an important research field for researchers. However, it gives a great velocity control challenge due to the complex nonlinearity, high coupling, and unique end effects. In this article, an improved model-free adaptive sliding-mode-constrained control method is proposed to deal with this problem dispensing with internal parameters of the LIM. Firstly, an improved compact form dynamic linearization (CFDL) technique is used to simplify the LIM plant. Besides, an antiwindup compensator is applied to handle the problem of the actuator under saturations in case during the controller design. Furthermore, the stability of the closed system is proved by Lyapunov stability method theoretically. Finally, simulation results are given to demonstrate that the proposed controller has excellent dynamic performance and stronger robustness compared with traditional PID controller.

scholarly journals Adaptive PD Sliding Mode Control For 4 DOF SCARA Variant

2021 ◽  
Author(s):  
Manjeet Tummalapalli
Keyword(s):  
Sliding Mode Control ◽  
Trajectory Tracking ◽  
High Speed ◽  
Sliding Mode ◽  
Adaptive Controller ◽  
Degree Of Freedom ◽  
Tracking Performance ◽  
Advantages And Disadvantages ◽  
Model Free ◽  
Adaptive Law

This project proposes a new SCARA variant with 4 degree of freedom. The proposed variant is achieved by swapping joint 2 and joint 3 of the standard SCARA robots. An adaptive controller is defined based on the advantages and disadvantages of PD, and SMC controllers.The purpose of the project is to understand the dynamics of the variant and to track the performance for trajectories. Simulations for tracking performance are carried under linear and circular trajectories. The variant is studied over the three controllers; PD, PD-SMC and A-PD-SMC. The variant under the adaptive controller is most efficient in terms of tracking performance and the control inputs to the system. The system is simulated under high speed and with the influence of friction at the joints. The control gains are held constant for both the trajectories and hence the controller is able to perform good under changing trajectories. Due to the use of the adaptive law, the system is at the ease of implementation and since no priori knowledge if the system is needed, it is model free. Therefore, the proposed adaptive PD-SMC has proven to provide good, robust trajectory tracking.

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