ZMP Theory-based Gait Planning and Model-Free Trajectory Tracking Control of Lower Limb Carrying Exoskeleton System

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.

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Data-Driven Adaptive Disturbance Observers for Model-Free Trajectory Tracking Control of Maritime Autonomous Surface Ships

IEEE Transactions on Neural Networks and Learning Systems ◽

10.1109/tnnls.2021.3093330 ◽

2021 ◽

pp. 1-11

Author(s):

Zhouhua Peng ◽

Dan Wang ◽

Jun Wang

Keyword(s):

Trajectory Tracking ◽

Tracking Control ◽

Data Driven ◽

Trajectory Tracking Control ◽

Model Free

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Trajectory tracking control of quadrotor under variable payloads with model-free controller and sliding mode control technology

Aircraft Engineering and Aerospace Technology ◽

10.1108/aeat-12-2020-0312 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Xu Zou ◽

Zhenbao Liu ◽

HongGang Gao ◽

Wen Zhao

Keyword(s):

Trajectory Tracking ◽

Tracking Control ◽

Sliding Mode ◽

Control Technique ◽

Variable Load ◽

Environmental Disturbance ◽

Trajectory Tracking Control ◽

Content Type ◽

Model Free ◽

Model Free Control

Purpose This study aims to deal with the problem of trajectory tracking control for the quadrotor under external environmental disturbance and variable payloads. Design/methodology/approach In the field of unmanned aerial vehicle (UAV) control, external environmental disturbance and internal variable payloads as two major interference factors lead to control performance degradation or even instability, thus a trajectory tracking controller which innovatively combines sliding mode control technology and model-free control technique is proposed. The proposed controller is constructed with a learning rate-based sliding mode controller and an ultra-local model. Based on the proposed controller, the nonlinear system model of variable load quadrotor is locally estimated and the system’s uncertainties and disturbances can be compensated. Findings The simulation and actual test results demonstrate the satisfactory control performance and the robustness of the proposed controller compared with the PID and Backstepping controller under external environmental disturbance and variable payloads. Moreover, the proposed controller solves the trajectory tracking control problem not only when payloads change at the center of gravity but also when the position of load variation deviates from the center of gravity. Practical implications In both military and civilian domains, the quadrotor may encounter such situations that the payloads change, such as transporting goods, aerial refueling and so on. As a large internal interference factor, variable load tends to lead to unstable control. The research results provide theoretical guidance and technical support for trajectory tracking control of quadrotor under variable payloads. Originality/value The proposed controller combines learning rate-based sliding mode controller and model-free control technique to achieve a more efficient and accurate trajectory control of the quadrotor when considering system uncertainties and the load variation that happens in the unknown location.

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