Fuzzy Sliding-Mode Formation Control for Multiple Underactuated Autonomous Underwater Vehicles
Being a benchmark for autonomous oceanic inspections, long-distance and long-duration surveys, underwater vehicles formation has attracted increasingly attentions on great application potentials. In order to realize formation control for under-actuated AU
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Abstract. Being a benchmark for autonomous oceanic inspections, long-distance and long-duration surveys, underwater vehicles formation has attracted increasingly attentions on great application potentials. In order to realize formation control for under-actuated AUVs, sliding mode formation control method has been applied on the basis of the AUV’s kinematic model. Fuzzy logic system is helpful to maintain formation shape for underactuated AUVs. In the simulations, under-actuated AUV characteristics have been analyzed during the first simulation. In the combination with fuzzy sliding-mode formation control and velocity limits, the controller has successfully realized 3D fold line formation and screw line formation. Therefore the fuzzy sliding-mode formation control strategy for under-actuated AUVs has been verified through the simulations. Keywords: Formation control
Underwater vehicles Underactuated
1 Introduction Multi-robot cooperation is a spontaneous attribute which has drawn significant attentions [1]. Recently since unmanned oceanic vehicles have been systematically researched, cooperative control of multiple Autonomous underwater vehicles (MAUVs) is playing more and more important role in performing underwater tasks, such as ocean sampling, mapping, minesweeping and ocean floor survey [2]. Carrying out MAUVs cooperation missions can increase efficiency and service area, and providing redundancy in case of failure [3]. In compare with one expensive specialized AUV, relatively inexpensive, simple, and small AUVs can solve difficult or complex underwater tasks more quickly. However, Multi-AUVs formation control is interconnected systems with complex dynamics. In compare with wireless communication on the land, acoustic communications has its own limitations such as information propagating with large delays, the speed of sound varies with depth, salinity, the underwater communication channel is very noisy, and transducers for acoustic communications are half duplex. In the past decade, considerable efforts have been carried out upon the formation control of MAUVs. Various approaches have been proposed, ranging from synchronized path following framework [4], and leader-follower mechanisms [2], to behavioral approach [5]. Since MAUVs formation confronts dynamics uncertainties such as payload © Springer International Publishing Switzerland 2016 Y. Tan et al. (Eds.): ICSI 2016, Part II, LNCS 9713, pp. 503–510, 2016. DOI: 10.1007/978-3-319-41009-8_54
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variations, hydrodynamics and time-varying oceanic currents, adaptive formation control methods have been suggested to deal with this problem [6]. These approaches allow decentralized implementation and it is natural to deduce control strategies when the robots have multiple competing objects. The algorithms usually required artificial potential trenches to realize the formation scalability [7]. For example, the cross-tracking control was proposed by using potential shaping [8]. Moreover, since most AUVs are underactuated, nonlinear path following
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