scholarly journals Event‐triggered adaptive fuzzy bipartite consensus control of multiple autonomous underwater vehicles

2020 ◽  
Vol 14 (20) ◽  
pp. 3632-3642
Author(s):  
Yuanyuan Xu ◽  
Tieshan Li ◽  
Shaocheng Tong
Keyword(s):  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Consensus Control ◽  
Adaptive Fuzzy ◽  
Bipartite Consensus ◽  
Event Triggered

scholarly journals Adaptive fuzzy depth control with trajectory feedforward compensator for autonomous underwater vehicles

2019 ◽  
Vol 11 (3) ◽  
pp. 168781401983817 ◽  
Author(s):  
Yuan Chen ◽  
Kangling Wang ◽  
Wei Chen
Keyword(s):  
Dead Zone ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Feedback Gain ◽  
Control Loop ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Adaptive Fuzzy ◽  
Fuzzy Compensator ◽  
Computed Torque

This article presents a computed-torque controller plus adaptive fuzzy trajectory feedforward compensator suitable for the trajectory tracking control of uncertain underwater vehicle. To address the issue of unavailable normalization factor, an adaptive fuzzy trajectory feedforward compensator is proposed and assembled at the input trajectory level of the computed-torque controller rather than at the joint drive torque position. The compensator serving as a low-pass filter is implemented outside the inner control loop by adjusting the desired characteristic depth. Due to the nearly unchanged internal control algorithm, the adaptive fuzzy compensator is feasible to implement and is robust when varying the feedback gain in the inner control loop. Moreover, an adaptive dead zone fuzzy compensator is designed to reduce the effect of the dead zone on the actuators of underwater vehicles according to the unknown input dead zone characteristics. To validate the effectiveness of the proposed controller, simulations are conducted for a desired characteristic depth, and the performance of the proposed controller has been compared with conventional controllers to illustrate the usefulness and efficiency of the proposed controller.

scholarly journals Distributed Finite-Time Bipartite Consensus for Multiagent System with Event-Triggered Control

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Haibo Xie ◽  
Zhengjiang Liu ◽  
Chengyong Yan ◽  
Shibo Zhou
Keyword(s):  
Finite Time ◽  
Control Method ◽  
Initial State ◽  
Consensus Control ◽  
Whole Process ◽  
Time Control ◽  
Consensus Values ◽  
Bipartite Consensus ◽  
Necessary And Sufficient ◽  
Event Triggered

This paper investigates the distributed finite-time event-triggered bipartite consensus control for multiagent systems over antagonistic networks. Under the constraint of energy conservation, a distributed nonlinear finite-time control protocol only depending upon local information is proposed coupled with event-triggered strategies, where controllers of agents at triggered instants are only updated to reduce the computation. It is proved that when the antagonistic network is structurally balanced with a spanning tree, a necessary and sufficient condition is established to guarantee all agents to reach consensus values with identical magnitude but opposite signs. More interestingly, the settling time depending on the initial state is obtained over the whole process. Comparing to asymptotic control algorithms, the proposed control method has better disturbance rejection properties and convergence rate. Simulations are given to demonstrate the effectiveness of the theoretical results.

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
Keyword(s):  
Sliding Mode ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Mass Variation ◽  
Content Type ◽  
Adaptive Fuzzy ◽  
Adaptive Fuzzy Sliding Mode ◽  
Fuzzy Sliding Mode ◽  
Payload Mass ◽  
Adaptive Smc

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.

scholarly journals Event-Based Secure Consensus of Multiple AUVs Under DoS Attacks

2021 ◽  
Author(s):  
Lizuo Wen ◽  
Shuanghe Yu ◽  
Ying Zhao ◽  
Yan Yan
Keyword(s):  
Autonomous Underwater Vehicles ◽  
Denial Of Service ◽  
Underwater Vehicles ◽  
Cyber Attack ◽  
Dos Attacks ◽  
Triggering Mechanism ◽  
Secure Control ◽  
Control Target ◽  
Event Based ◽  
Event Triggered

Abstract In this paper, the event-based triggering method is adopted to investigate the secure consensus issue of multiple autonomous underwater vehicles (AUVs) under denial-of-service (DoS) attacks. DoS attack is a form of time-sequence-based cyber attack, which can destroy the normal service of the control target or network. First, based on an event-triggered mechanism, a novel secure control protocol is proposed. Second, the upper bounds of attack duration and attack frequency are given to ensure that multiple AUVs under DoS attacks can reach consensus. Third, an event-triggered mechanism with exponential variables is developed to avoid the continuous update of the controller, thereby reducing the burdens of communication and calculation. Zeno behavior can be strictly ruled out for each AUV under this triggering mechanism. Finally, the simulation results illustrate the feasibility of the proposed scheme.

Sign in / Sign up

Export Citation Format

Share Document