Adaptive fuzzy sliding mode formation controller for autonomous underwater vehicles with variable payload

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.

2019 ◽  
Vol 12 (1) ◽  
pp. 102-126 ◽  
Author(s):  
Hanène Medhaffar ◽  
Moez Feki ◽  
Nabil Derbel

Purpose The purpose of this paper is to investigate the stabilization of unstable periodic orbits of Chua’s system using adaptive fuzzy sliding mode controllers with moving surface. Design/methodology/approach For this aim, the sliding mode controller and fuzzy systems are combined to achieve the stabilization. Then, the authors propose a moving sliding surface to improve robustness against uncertainties during the reaching phase, parameter variations and extraneous disturbances. Findings Afterward, the authors design a sliding observer to estimate the unmeasurable states which are used in the previously designed controller. Originality/value Numerical results are provided to show the effectiveness and robustness of the proposed method.


Author(s):  
Jun He ◽  
Minzhou Luo ◽  
Xinglong Zhang ◽  
Marco Ceccarelli ◽  
Jian Fang ◽  
...  

Purpose This paper aims to present an adaptive fuzzy sliding mode controller with nonlinear observer (AFSMCO) for the redundant robotic manipulator handling a varying payload to achieve a precise trajectory tracking in the task space. This approach could be applied to solve the problems caused by the dynamic effect of the varying payload to robotic system caused by model uncertainties. Design/methodology/approach First, a suitable observer using the recursive algorithm is presented for an accurate estimation of external disturbances caused by a variable payload. Second, the adaptive fuzzy logic is designed to approximate the parameters of the sliding mode controller combined with nonlinear observer (SMCO) to avoid chattering in real time. Moreover, Lyapunov theory is applied to guarantee the stability of the proposed closed-loop robotic system. Finally, the effectiveness of the proposed control approach and theoretical discussion are proved by simulation results on a seven-link robot and demonstrated by a humanoid robot platform. Findings The varying payload leads to large variations in the dynamics of the manipulator and the tracking error. To achieve high-precision position tracking, nonlinear observer was introduced to feed into the sliding mode control (SMC) which had improved the ability to resist the external disturbance. In addition, the chattering caused by the SMC was eliminated by recursively approximating the switching gain with the usage of adaptive fuzzy logic. Therefore, a distributed control strategy solves the problems of an SMC implementation in improving its tracking performance and eliminating the chattering of the system control. Originality/value The AFSMCO is proposed for the first time and used to control the redundant robotic manipulator that handles the varying payload. The proposed control algorithm possesses better robustness and higher precision for the trajectory tracking than classical SMC.


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