Modeling and Three-Layer Adaptive Diving Control of a Cable-Driven Underwater Parallel Platform

This paper focuses on the modeling, diving controller design, and experiment of a special cable-driven underwater parallel platform with eight-cable coupling drive structure. Kinematic and dynamic models of the platform are established utilizing a simplified approach, and the hydraulic driven control model is derived based on joint-space method. To improve the diving control precision and system robustness despite the complex dynamic behaviors and manifold unknown disturbances, a three-layer adaptive diving control strategy is proposed. Among the three control layers, layer 1 is responsible for dive planning and online monitoring, layer 2 places emphasis on synchronous control by employing an improved relative coupling strategy, layer 3 utilizes an adaptive radial basis function neural network-based backstepping sliding mode control algorithm (ARBFNN-BSMC) to achieve high precision speed control of the single driving branch. Hardware-in-the-loop simulations and experimental results illustrate that the proposed three-layer adaptive diving control strategy can asymptotically drive the cable-driven underwater parallel platform onto a predefined diving trajectory with favorable precision, robustness, and stability.

[1]  Christopher T. Orlowski,et al.  Dynamics, stability, and control analyses of flapping wing micro-air vehicles , 2012 .

[2]  Philippe Martinet,et al.  Dynamic modeling of parallel robots with flexible platforms , 2014 .

[3]  Saeed Tavakoli,et al.  Delayed adaptive output feedback sliding mode control for offshore platforms subject to nonlinear wave-induced force , 2015 .

[4]  Hongwen He,et al.  Analysis of the Performance of Aerial Work Platform Working Device Based on Virtual Prototype and Finite Element Method , 2016 .

[5]  Xianbo Xiang,et al.  Dynamics and control of underwater tension leg platform for diving and leveling , 2015 .

[6]  P. D. Shendge,et al.  Disturbance observer based sliding mode control of nonlinear mismatched uncertain systems , 2015, Commun. Nonlinear Sci. Numer. Simul..

[7]  Haoping Wang,et al.  Trajectory Tracking Control of XY Table Using Sliding Mode Adaptive Control Based on Fast Double Power Reaching Law , 2016 .

[8]  Khoshnam Shojaei,et al.  Neural network formation control of underactuated autonomous underwater vehicles with saturating actuators , 2016, Neurocomputing.

[9]  Qin Zhang,et al.  On intelligent risk analysis and critical decision of underwater robotic vehicle , 2017 .

[10]  Thor I. Fossen,et al.  Guidance and control of ocean vehicles , 1994 .

[11]  Jooyoung Park,et al.  Universal Approximation Using Radial-Basis-Function Networks , 1991, Neural Computation.

[12]  Belhassen Chedli Bouzgarrou,et al.  Static and dynamic characterization of the 6-Dofs parallel robot 3CRS , 2015 .

[13]  Mehmet Mutlu,et al.  Lagrangian based mathematical modeling and experimental validation of a planar stabilized platform for mobile systems , 2014, J. Comput. Appl. Math..

[14]  Bidyadhar Subudhi,et al.  Nonlinear H∞ Control for an Autonomous Underwater Vehicle in the Vertical Plane , 2016 .

[15]  Xinghuo Yu,et al.  Integral sliding mode control for offshore steel jacket platforms , 2012 .

[16]  Alireza Khosravi,et al.  Model reference adaptive autopilot with anti-windup compensator for an autonomous underwater vehicle: Design and hardware in the loop implementation results , 2017 .

[17]  Mahir Hassan,et al.  Workspace analysis of a Gough-Stewart type cable marine platform subjected to harmonic water waves , 2018 .

[18]  Jun Wu,et al.  Mechatronics modeling and vibration analysis of a 2-DOF parallel manipulator in a 5-DOF hybrid machine tool , 2018 .

[19]  Honghai Liu,et al.  Adaptive Sliding-Mode Control for Nonlinear Active Suspension Vehicle Systems Using T–S Fuzzy Approach , 2013, IEEE Transactions on Industrial Electronics.

[20]  Chun Zhang,et al.  Adaptive reaching law based sliding mode control for electromagnetic formation flight with input saturation , 2016, J. Frankl. Inst..

[21]  Bikash Kumar Sarkar.  Modeling and validation of a 2-DOF parallel manipulator for pose control application , 2018 .

[22]  Sergej Fatikow,et al.  Modeling and controller design of a 6-DOF precision positioning system , 2018 .

[23]  Georg Nawratil.  Stewart Gough platforms with non-cubic singularity surface , 2010 .

[24]  Xusheng Lei,et al.  An adaptive decoupling control for three-axis gyro stabilized platform based on neural networks , 2015 .

[25]  Christopher Edwards,et al.  Adaptive continuous higher order sliding mode control , 2016, Autom..

[26]  Shuai Li,et al.  Simultaneous learning and control of parallel Stewart platforms with unknown parameters , 2017, Neurocomputing.

[27]  Li-Chen Fu,et al.  Observer-based backstepping control of a 6-dof parallel hydraulic manipulator , 2015 .

[28]  Qin Zhang,et al.  On decentralized adaptive full-order sliding mode control of multiple UAVs. , 2017, ISA transactions.

[29]  Juan Li,et al.  Observer-based optimal fault-tolerant control for offshore platforms , 2014, Comput. Electr. Eng..

[30]  Herbert Martins Gomes,et al.  A smart force platform using artificial neural networks , 2016 .

[31]  B. Jouvencel,et al.  Robust Nonlinear Path-Following Control of an AUV , 2008, IEEE Journal of Oceanic Engineering.