An adaptive sliding mode controller with a new reaching law for tracking problem of an autonomous underwater vehicles

2018 ◽  
Vol 41 (6) ◽  
pp. 1772-1787 ◽  
Author(s):  
Mohammad Reza Ramezani-al ◽  
Zahra Tavanaei-Sereshki

Since autonomous underwater vehicles (AUVs) have highly nonlinear dynamics, the employed controller in these systems must be accurate and robust against noise and uncertainties. Sliding Mode Controller is very robust against both the parameters changing and external disturbance. But, there are some major drawbacks of these controllers such as chattering and high vulnerability against noise. In this paper, by modifying the reaching law and using an adaptive gain in the proposed sliding mode controller, these problems are eliminated from the input signal of the system. In the presented reaching law, a continuous term is used instead of the discrete sign function as well as the velocity term is entered in the reaching law. Since there are external disturbances, noises and uncertainties in the system dynamics and modeling, the states may be separated from the surface. Since the reaching law acts when the states separate from the sliding surface, then the gain of reaching law is adapted according to the uncertainties, states error and velocity. Also, the upper bound of disturbance and uncertainty are estimated. Furthermore, the reaching condition and limitation of the switching variable rate for the proposed controller are investigated. Finally, stability and convergence of the closed-loop system are proven analytically using the Lyapunov stability theorem. Some simulations and comparisons with other methods show efficiency of the presented method.

2013 ◽  
Vol 67 (1) ◽  
pp. 113-127 ◽  
Author(s):  
Daqi Zhu ◽  
Xun Hua ◽  
Bing Sun

A biologically inspired neurodynamics-based tracking controller of underactuated Autonomous Underwater Vehicles (AUV) is proposed in this paper. The proposed control strategy includes a velocity controller with biological neurons and an adaptive sliding mode controller. The biological neurons are embedded into the backstepping velocity controller to eliminate the sharp speed jumps commonly existing in vehicles due to tracking errors changing suddenly. The outputs of the velocity controller are used as the command inputs of the sliding mode controller, and the thruster control constraints problems that are commonly seen in the backstepping control of AUV are solved by the proposed controller. Simulation results show that the control strategy achieved success in smoothly tracking AUV position and velocity.


2021 ◽  
Vol 39 (3A) ◽  
pp. 355-369
Author(s):  
Dina H. Tohma ◽  
Ahmed K. Hamoudi

This work aims to study and apply the adaptive sliding mode controller (ASMC) for the pendulum system with the existence of the parameters uncertainty, external disturbances, and coulomb friction. The adaptive sliding mode controller has several features over the conventional sliding mode control method. Firstly, the magnitude of the control signal is reduced to the minimally acceptable level defined by special conditions concerned with ASMC algorithm. Secondly, the upper bounds of uncertainties are not necessary to be defined before starting the work. For this reason, the ASMC can be used successfully to control the pendulum system with minimum control effort. These properties of the ASMC are confirming graphically by the simulation results using MATLAB 2019. The ASMC achieves an asymptotically stable system better than the Classical Sliding Mode Controller (CSMC). The unwanted phenomenon is called “chattering", which is appearing in the control action signal. These drawback properties are suppressed by employing a saturation function. Finally, the comparison between the results of the ASMC and CSMC showed that ASMC is the better one.


Author(s):  
Behzad Taheri ◽  
Edmond Richer

A new method of path planning and tracking while maintaining a constant distance from underwater moving objects has been developed for autonomous underwater vehicles (AUVs). First a kinematics controller that generates the proper trajectories is designed. Then a dynamics sliding mode controller is employed to drive the vehicle on the desired trajectories. The dynamics controller is robust against the parameter uncertainty in the dynamics model of the vehicle. Results of numerical simulations for INFANTE-AUV model show excellent performance for tracking of an object on sinusoidal trajectory.


2021 ◽  
Vol 18 (1) ◽  
pp. 172988142098708
Author(s):  
Ameni Azzabi ◽  
Khaled Nouri

This article propounds addressing the design of a sliding mode controller with adaptive gains for trajectory tracking of unicycle mobile robots. The dynamics of this class of robots are strong, nonlinear, and subject to external disturbance. To compensate the effect of the unknown upper bounded external disturbances, a robust sliding mode controller based on an integral adaptive law is proposed. The salient feature of the developed controller resides in taking into account that the system is MIMO and the upper bound of disturbances is not priori known. Therefore, we relied on an estimation of each perturbation separately for each subsystem. Hence, the proposed controller provides a minimum acceptable errors and bounded adaptive laws with minimum of chattering problem. To complete the goal of the trajectory tracking, we apply a kinematic controller that takes into account the nonholonomic constraint of the robot. The stability and convergence properties of the proposed tracking dynamic and kinematic controllers are analytically proved using Lyapunov stability theory. Simulation results based on a comparative study show that the proposed controllers ensure better performances in terms of good robustness against disturbances, accuracy, minimum tracking errors, boundness of the adaptive gains, and minimum chattering effects.


Robotica ◽  
2018 ◽  
Vol 36 (8) ◽  
pp. 1188-1205 ◽  
Author(s):  
Felix Orlando Maria Joseph ◽  
Tarun Podder

SUMMARYIn medical interventional procedures such as brachytherapy, biopsy and radio-frequency ablation, precise tracking through the preplanned desired trajectory is very essential. This important requirement is critical due to two major reasons: anatomical obstacle avoidance and accurate targeting for avoiding undesired radioactive dose exposure or damage to neighboring tissue and critical organs. Therefore, a precise control of the needling device in the unstructured environment in the presence of external disturbance is required to achieve accurate target reaching in clinical applications. In this paper, a shape memory alloy actuated active flexible needle controlled by an adaptive sliding mode controller is presented. The trajectory tracking performance of the needle is tested while having its actual movement in an artificial tissue phantom by giving various input reference trajectories such as multi-step and sinusoidal. Performance of the adaptive sliding mode controller is compared with that of the proportional, integral and derivative controller and is proved to be the effective method in the presence of the external disturbances.


2017 ◽  
Vol 40 (13) ◽  
pp. 3625-3639 ◽  
Author(s):  
Shiyu Chen ◽  
Jianping Yuan ◽  
Zheng Wang ◽  
Zhanxia Zhu

This paper aims to address the attitude stabilization issue of post-capture combination with underactuated actuators, measurement inaccuracy and unknown external disturbances during on-orbit servicing. A precise and practical form of underactuated attitude dynamics is proposed for the asymmetric combination with two control torques. With the adopted partial stabilization strategy, a sliding mode controller is first proposed to achieve partial stabilization of the combination against the effect of unknown external disturbances. Through the additional consideration of the measurement inaccuracy in the inertia tensor and the mass centroid, an underactuated adaptive sliding mode controller with compensation laws is proposed in presence of uncertainties and disturbances. Numerical simulations validate the effectiveness of proposed partial attitude stabilization controllers.


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