Enhanced dynamic fuzzy sliding mode controller for autonomous underwater vehicles

Author(s):  
G. V. Lakhekar ◽  
L. M. Waghmare ◽  
P. S. Londhe
2015 ◽  
Vol 18 (1) ◽  
pp. 14-26
Author(s):  
Tuong Quan Vo

The fish robot is a new type of biomimetic underwater robot which is developing very fast in recent years by many researchers. Because it moves silently, saves energy, and is flexible in its operation in comparison to other kinds of underwater robots, such as Remotely Operated Vehicles (ROVs) or Autonomous Underwater Vehicles (AUVs). In this paper, we propose an efficient advanced controller that runs well in controlling the motion for our fish robot. First, we derive a new dynamic model of a 3-joint (4 links) Carangiform fish robot. The dynamic model also addresses the heading angle of a fish robot, which is not often covered in other research. Second, we present a Sliding Mode Controller (SMC) and a Fuzzy Sliding Mode Controller (FSMC) to the straight motion and turning motion of a fish robot. Then, in order to prove the effectiveness of the SMC and FSMC, we conduct some numerical simulations to show the feasibility or the advantage of these proposed controllers.


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.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Madhusmita Panda ◽  
Bikramaditya Das ◽  
Bidyadhar Subudhi ◽  
Bibhuti Bhusan Pati

PurposeIn this paper, an adaptive fuzzy sliding mode controller (AFSMC) is developed for the formation control of a team of autonomous underwater vehicles (AUVs) subjected to unknown payload mass variations during their mission.Design/methodology/approachA sliding mode controller (SMC) is designed to drive the state trajectories of the AUVs to a switching surface in the state space. The payload mass variation results in parameter variation in AUV dynamics leading to actuator failure. This further leads to loss of communication among the members of the team. Hence, an adaptive SMC based on fuzzy logic is developed to maintain the coordinated motion of AUVs with payload mass variation.FindingsThe results are obtained by employing adaptive SMC for AUVs with and without payload variations and are compared. It is observed that the proposed adaptive SMC exhibits improved performance and tracks the desired trajectory in less time even with variation in the payload. The adaptive fuzzy control algorithm is developed to handle variation in payload mass variation. Lyapunov theory is used to establish stability of AFSMC controller.Research limitations/implicationsPerfect alignment is assumed between centres of gravity (OG) and buoyancy (OB), thus AUVs maintaining horizontal stability during motion. The AUVs’ body centres are aligned with centres of gravity (OG), thus the distance vector being rg = [0,0,0]T. As it is a tracking problem, sway motion cannot be neglected as the AUVs are travelling in a curved locus, hence susceptible to Coriolis and centripetal forces. The AUV is underactuated as only two thrusters at the stern plate that are employed for the surge and yaw controls and error in Y- direction are controlled by adjusting control input in surge and heave direction. Control inputs to the thruster are constants, and depth control is achieved by adjusting the rudder angle.Practical implicationsAUVs are employed in military mission or surveys, and they carry heavy weapons or instrument to be deployed at or picked from specific locations. Such tasks lead to variation in payload, causing overall mass variation during an AUV’s motion. A sudden change in the mass after an AUV release or pick load results in variation in depth and average velocity.Social implicationsThe proposed controller can be useful for military missions for carrying warfare and hydrographic surveys for deploying instruments.Originality/valueA proposed non-linear SMC has been designed, and its performances have been verified in terms of tracking error in X, Y and Z directions. An adaptive fuzzy SMC has been modelled using quantized state information to compensate payload variation. The stability of AFSMC controller is established by using Lyapunov theorem, and reachability of the sliding surface is ensured.


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.


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