Wyniki wyszukiwania - BazTech

1

Robust H∞ fuzzy approach design via Takagi‐Sugeno descriptor model. application for 2‐DOF serial manipulator tracking control

Thi Van Anh Nguyen, Pham Duc Binh, Nguyen Danh Huy, Nguyen Tung Lam

Journal of Automation Mobile Robotics and Intelligent Systems

|

2022

|

Vol. 16, No. 3

22--29

EN

This paper focuses on trajectory tracking control for ro‐ bot manipulators. While much research has been done on this issue, many other aspects of this field have not been fully addressed. Here, we present a new solution using feedforward controller to eliminate parametric uncer‐ tainties and unknown disturbances. The Takagi‐Sugeno fuzzy descriptor system (TSFDS) is chosen to describe the dynamic characteristics of the robot. The combination of this fuzzy system and the robust H∞ performance makes the system almost isolated from external factors. The li‐ near matrix inequalities based on the theory of Lyapunov stability is considered for control design. The proposed method has proven its effectiveness through simulation results.

2

State observer-based backstepping sliding mode control for electro-hydraulic systems

Tan Tan, Duc Nguyen Quang, Minh Le Ngoc, Manh Cuong Nguyen, Nguyen Danh Huy, Nguyen Tung Lam

Annals of Computer Science and Information Systems

|

2021

|

Vol. 27

77-80

EN

In the paper, a control method using backstepping integrated with sliding mode control based on high-gain observer is proposed for an Electro-Hydraulic system (EHS). The observer is dedicated to estimate full-state variables by using output position feedback. In the initial step, the control design formula is constructed via backstepping technique. Following that, the control signal is designed based on sliding mode control (SMC) algorithm, and thus lead to the controller that has the advantages of these two control laws.

3

Mobile robots interacting with obstacles control based on artificial intelligence

Chuyen Tran Duc, Hoa Roan Van, Dien Nguyen Duc, Nguyen Tung Lam

Annals of Computer Science and Information Systems

|

2021

|

Vol. 27

13--16

EN

In this paper, research on the applications of artificial intelligence in implementing Deep Deterministic Policy Gradient (DDPG) on Gazebo model and the reality of mobile robot has been studied and applied. The goal of the experimental studies is to navigate the mobile robot to learn the best possible action to move in real-world environments when facing fixed and mobile obstacles. When the robot moves in an environment with obstacles, the robot will automatically control to avoid these obstacles. Then, the more time that can be maintained within a specific limit, the more rewards are accumulated and therefore better results will be achieved. The authors performed various tests with many transform parameters and proved that the DDPG algorithm is more efficient than algorithms like Q-learning, Machine learning, deep Q-network, etc. Then execute SLAM to recognize the robot positions, and virtual maps are precisely built and displayed in Rviz. The research results will be the basis for the design and construction of control algorithms for mobile robots and industrial robots applied in programming techniques and industrial factory automation control.

4

Control design of an UAV–Q based on feedback linearization and optimum modulus methods

Chuyen Tran Duc, Huy Hoang Van, Nguyen Tung Lam

Annals of Computer Science and Information Systems

|

2021

|

Vol. 27

17--22

EN

In the paper, we present the formulation of quadrotor control loops that are based on a decomposition into a cascade structure and the use of feedback linearization and optimum modulus methods to determine controller parameters. The dynamic model used in this paper considers the dynamics of the propeller rotor drive systems. The propeller rotor drive systems are considered as a linear actuated system. After the synthesizing of the controllers is completed, the system is simulated in MATLAB/Simulink. The results from this work can be useful for the development of autonomous algorithms for UAV-Q (Unmanned Aerial Vehicle Quadrotor). The research results serve as the basis for control algorithms development for other similar systems.