Trajectory Tracking Control of Hypersonic Reentry Vehicle Based on Adaptive Fuzzy System

2012 ◽  
Vol 236-237 ◽  
pp. 378-384
Author(s):  
Bo Yang ◽  
Yuan Chao Wang
Keyword(s):  
Fuzzy Control ◽  
Trajectory Tracking ◽  
Fuzzy System ◽  
Tracking Control ◽  
Control Method ◽  
Trajectory Tracking Control ◽  
Reentry Vehicle ◽  
Adaptive Tracking Control ◽  
Adaptive Tracking ◽  
Fuzzy Adaptive

Considering inaccurate model and simplified calculation problems of the hypersonic reentry vehicle, this paper presents an adaptive fuzzy control system of the trajectory tracking control method. Firstly we introduced the principle of fuzzy system, then used fuzzy control theory to approximate the second-order drag acceleration model and got drag model by fuzzy identification, finally designed the adaptive controller. The simulation results show that the fuzzy adaptive tracking control method don’t depend on the dynamic model, but only rely on drag of the vehicle suffered, it can be measured directly or obtained by the aerodynamic model of the flight, the can generate tracking guidance control law, and the fuzzy adaptive tracking control method enables hypersonic vehicle to track the drag reference trajectory, realizes safe reentry and the terminal states can meet the requirements of the terminal constraints with high precision.

Robust finite-time trajectory tracking control for a space manipulator with parametric uncertainties and external disturbances

2021 ◽  
pp. 095441002110147
Author(s):  
Qijia Yao
Keyword(s):  
Trajectory Tracking ◽  
Finite Time ◽  
Tracking Control ◽  
Disturbance Observer ◽  
Control Method ◽  
Parametric Uncertainties ◽  
External Disturbances ◽  
Trajectory Tracking Control ◽  
Space Manipulator ◽  
Tracking Controller

Space manipulator is considered as one of the most promising technologies for future space activities owing to its important role in various on-orbit serving missions. In this study, a robust finite-time tracking control method is proposed for the rapid and accurate trajectory tracking control of an attitude-controlled free-flying space manipulator in the presence of parametric uncertainties and external disturbances. First, a baseline finite-time tracking controller is designed to track the desired position of the space manipulator based on the homogeneous method. Then, a finite-time disturbance observer is designed to accurately estimate the lumped uncertainties. Finally, a robust finite-time tracking controller is developed by integrating the baseline finite-time tracking controller with the finite-time disturbance observer. Rigorous theoretical analysis for the global finite-time stability of the whole closed-loop system is provided. The proposed robust finite-time tracking controller has a relatively simple structure and can guarantee the position and velocity tracking errors converge to zero in finite time even subject to lumped uncertainties. To the best of the authors’ knowledge, there are really limited existing controllers can achieve such excellent performance under the same conditions. Numerical simulations illustrate the effectiveness and superiority of the proposed control method.

Dynamic trajectory-tracking control method of robotic transcranial magnetic stimulation with end-effector gravity compensation based on force sensors

2018 ◽  
Vol 45 (6) ◽  
pp. 722-731
Author(s):  
ZeCai Lin ◽  
Wang Xin ◽  
Jian Yang ◽  
Zhang QingPei ◽  
Lu ZongJie
Keyword(s):  
Neural Networks ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Magnetic Stimulation ◽  
Control Method ◽  
Gravity Compensation ◽  
Trajectory Tracking Control ◽  
End Effector ◽  
Content Type ◽  
Dynamic Trajectory

Purpose This paper aims to propose a dynamic trajectory-tracking control method for robotic transcranial magnetic stimulation (TMS), based on force sensors, which follows the dynamic movement of the patient’s head during treatment. Design/methodology/approach First, end-effector gravity compensation methods based on kinematics and back-propagation (BP) neural networks are presented and compared. Second, a dynamic trajectory-tracking method is tested using force/position hybrid control. Finally, an adaptive proportional-derivative (PD) controller is adopted to make pose corrections. All the methods are designed for robotic TMS systems. Findings The gravity compensation method, based on BP neural networks for end-effectors, is proposed due to the different zero drifts in different sensors’ postures, modeling errors in the kinematics and the effects of other uncertain factors on the accuracy of gravity compensation. Results indicate that accuracy is improved using this method and the computing load is significantly reduced. The pose correction of the robotic manipulator can be achieved using an adaptive PD hybrid force/position controller. Originality/value A BP neural network-based gravity compensation method is developed and compared with traditional kinematic methods. The adaptive PD control strategy is designed to make the necessary pose corrections more effectively. The proposed methods are verified on a robotic TMS system. Experimental results indicate that the system is effective and flexible for the dynamic trajectory-tracking control of manipulator applications.

Group Control of Mobile Robots for More Efficient Searches – Verification of Semi-Autonomous Trajectory Tracking Motions in Irregular Ground Environment –

2018 ◽  
Vol 30 (6) ◽  
pp. 980-990
Author(s):  
Yoshikazu Ohtsubo ◽  
Morihito Matsuyama ◽  
◽  
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Control Method ◽  
Potential Method ◽  
Gravity Potential ◽  
Trajectory Tracking Control ◽  
Robot Operating System ◽  
Uneven Terrain ◽  
Disaster Area ◽  
Autonomous Search

After the occurrence of a disaster, it is critical to perform rapid and accurate searching operations in the large disaster area. It is efficient to perform such operations using multiple mobile exploration robots. Accordingly, we focus on cooperative cruising in a disaster environment and propose the trajectory tracking control method for a semi-autonomous search robot. We apply a robot operating system (ROS) to execute the trajectory tracking control using two mobile exploration robots. In this paper, we describe the trajectory tracking control using gravity potential method and the results of a cooperative cruising experiment in an uneven terrain environment.

Sign in / Sign up

Export Citation Format

Share Document