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.

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.

Model-free adaptive iterative sliding mode control for a robotic exoskeleton trajectory tracking system

2020 ◽  
Vol 51 (10) ◽  
pp. 1782-1797
Author(s):  
Xuechao Qiu ◽  
Changchun Hua ◽  
Jiannan Chen ◽  
Liuliu Zhang ◽  
Xinping Guan
Keyword(s):  
Sliding Mode Control ◽  
Trajectory Tracking ◽  
Sliding Mode ◽  
Tracking System ◽  
Robotic Exoskeleton ◽  
Mode Control ◽  
Model Free

Trajectory-following of a 4WID-4WIS vehicle via feedforward–backstepping sliding-mode control

2021 ◽  
pp. 095440702110212
Author(s):  
Yu-long Lei ◽  
Guanzheng Wen ◽  
Yao Fu ◽  
Xingzhong Li ◽  
Boning Hou ◽  
...  
Keyword(s):  
Sliding Mode Control ◽  
Trajectory Tracking ◽  
Degrees Of Freedom ◽  
Sliding Mode ◽  
Tracking Performance ◽  
Luenberger Observer ◽  
Mode Control ◽  
Comprehensive Method ◽  
Backstepping Sliding Mode Control ◽  
Flexible Operation

Realisation of high-precision trajectory tracking is the key technology to achieve unmanned driving, which has an important impact on vehicle handling stability, safety and comfort. However, many confounding factors seriously restrict tracking performance and pose a great challenge to the design of the controller for tracking the desired trajectory. A comprehensive method that combines feedforward and backstepping sliding mode control is proposed for a four-wheel independent driving–four-wheel independent steering (4WID-4WIS) vehicle, which has the advantages of over-coupling, multiple degrees of freedom and flexible operation. The desired value is the target for the feedforward output of the controller, and the backstepping sliding mode control is used to overcome all kinds of disturbances. A mature and reliable Luenberger observer is designed to achieve good trajectory tracking performance for reducing some sensors. The proposed method is verified via MATLAB/Simulink simulation, which proved that the method has an excellent trajectory tracking performance.

scholarly journals Model-free control of a quadrotor using adaptive proportional derivative-sliding mode control and robust integral of the signum of the error

2018 ◽  
Vol 15 (5) ◽  
pp. 172988141880088 ◽  
Author(s):  
Zhi Li ◽  
Xin Ma ◽  
Yibin Li
Keyword(s):  
Sliding Mode Control ◽  
Trajectory Tracking ◽  
Sliding Mode ◽  
Three Dimensional ◽  
Lyapunov Stability Theory ◽  
Trajectory Tracking Control ◽  
Loop Control ◽  
Mode Control ◽  
Model Free ◽  
Asymptotic Tracking

In this article, a robust model-free trajectory tracking control strategy is developed for a quadrotor in the presence of external disturbances. The proposed strategy has an outer-inner-loop control structure. The outer loop controls the position with adaptive proportional derivative-sliding mode control and generates the desired attitude angles for the inner loop corresponding to the given position, velocity, and heading references, while the robust integral of the signum of the error method is applied to the inner loop to guarantee fast convergence of attitude angles. Asymptotic tracking of the three-dimensional trajectories is proven by the Lyapunov stability theory. The effectiveness of the proposed controller is demonstrated with the simulation results by comparing with other model-free quadrotor trajectory tracking controllers.

scholarly journals Double-Loop Sliding Mode Controller with An Ocean Current Observer for the Trajectory Tracking of ROV

2021 ◽  
Vol 9 (9) ◽  
pp. 1000
Author(s):  
Weilei Mu ◽  
Yuxue Wang ◽  
Hailiang Sun ◽  
Guijie Liu
Keyword(s):  
Sliding Mode Control ◽  
Trajectory Tracking ◽  
Sliding Mode ◽  
Tracking Performance ◽  
Ocean Current ◽  
Sliding Mode Controller ◽  
Double Loop ◽  
Mode Control ◽  
Reference Velocity ◽  
Attitude Tracking

To solve the trajectory tracking problem of insufficient response and the large tracking error of remotely operated vehicles (ROVs) under the interference of large ocean currents, this paper proposes a double-loop sliding mode controller with an ocean current observer. The designed controller consisted of an outer-loop controller (the position controller) and an inner-loop controller (the velocity controller): the outer controller was designed by the position error, and a reference velocity was created for the inner loop to achieve accurate positioning and attitude tracking. The reference control input was treated as a new target to design the inner-loop controller, enabling the ROV to achieve accurate reference velocity tracking. Based on the theoretical idea of active disturbance rejection control, a kinematic equation-based ocean current observer was designed to estimate and compensate for large unknown currents to ensure accurate trajectory tracking performance under large currents. The simulation results proved that the double-loop sliding-mode control scheme with an ocean current observer always showed good tracking performance, demonstrating the excellent control performance and high robustness of the scheme. Compared with the high-complexity control schemes such as neural network-based PID control or fuzzy sliding mode control, it effectively improves the robustness to ocean current disturbances without increasing the computational effort excessively, and is more practical in ROV systems with limited computational power.

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.

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