Nonlinear H∞ Control Algorithms for AutonomousUnderwater Vehicle in Diving and Steering Planes (original) (raw)
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The Nonlinear Suboptimal Diving Control of an Autonomous Underwater Vehicle
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2 MTAS ZTAKI, Hungarian Academyo fS cience,B udapest XI Kende u. 13-17, H-1518 Budapest,P OB 63, Hungary bokor@sztaki.hu 3 CivilE ngineeringa nd St.A nthony Falls Laboratory,2ThirdA ve.S E, Universityo fM innesota, Minneapolis, MN 55414 arndt001@umn.edu B.A. Francis et al. (Eds.): Control of Uncertain Systems, LNCIS 329, pp. 25-44, 2006.
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IFAC Proceedings Volumes, 2003
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Robustness of autonomous underwater vehicle control in variable working conditions
Journal of Marine Science and Technology, 2007
vehicles. Sliding mode control was one of the fi rst control methods implemented for underwater vehicles. 1 It has shown advantages in several implementations. 2,3 Different control methodologies used for underwater vehicles are categorized by Fossen. 4 In the work of Logan, 5 H ∞ /msynthesis methods are compared with the sliding mode method. A comparison of different control techniques, including artifi cial intelligence methods, is presented by Lea et al. 6 While H ∞ and m-synthesis methods can handle the discarded higher-order modes of a system, they may lead to conservative results in the computation of allowable variations in the parameters of the system to maintain stability, since the structure of the parameter uncertainty is not taken into account in these methods. 7,8 Considerable research effort has been invested in control of systems with uncertain parameters by using the properties of their characteristic polynomials. 8,9 In work by Ackermann, 9 the applicability of polynomial methods to the steering of ground-based and fl ying vehicles was demonstrated. When the characteristic polynomials of linear systems are linear functions of uncertain parameters, there exists a wide range of tools to deal with such systems. 8,9 However, when the coeffi cients of the characteristic polynomials are nonlinear or multilinear functions of the parameters, only few results are available. Several works on this subject are gathered in the books by Ackermann 9 and Djaferis. 10 In this article, an underwater vehicle, whose operating speed and hydrodynamic derivatives are subject to perturbations, was modeled as a plant with uncertain parameters. The vehicle under study is Naval Postgraduate School (NPS) Autonomous Underwater Vehicle (AUV) II that has been described by Healey and Leinard. 2 The effects of the uncertainty in the operating velocity Abstract The performance of the control systems of autonomous underwater vehicles (AUVs) in the presence of parameter variations was studied. With an AUV working at different operating speeds and in different ocean environments, the physical parameters such as speed, hydrodynamic coeffi cients, or inertias may be perturbed from their nominal values. The vehicle control systems can be modeled as systems with parameter uncertainty. An existing robust control method, which uses the robustness properties of polynomials, was used for this system to calculate the permissible ranges of variation in the parameters. The method was applied to the Naval Postgraduate School AUV II and the results were verifi ed by simulating the motion control of the vehicle under the infl uence of parameter perturbations.
Robust Tracking Control of Autonomous Underwater Vehicles in the Presence of Disturbance Inputs
An autonomous underwater vehicle (AUV) is expected to operate in an ocean in the presence of poorly known disturbance forces and moments. The uncertainties of the environment makes it difficult to apply open-loop control scheme for the motion planning of the vehicle. The objective of this paper is to develop a robust feedback trajectory tracking control scheme for an AUV that can track a prescribed trajectory amidst such disturbances. We solve a general problem of feedback trajectory tracking of an AUV in SE(3). The feedback control scheme is derived using Lyapunov-type analysis. The results obtained from numerical simulations confirm the asymptotic tracking properties of the feedback control law. We apply the feedback control scheme to different mission scenarios, with the disturbances being initial errors in the state of the AUV.
Autopilot control synthesis for path tracking maneuvers of underwater vehicles
China Ocean Engineering, 2011
This paper addresses the robust control synthesis of diving/climbing manoeuvres for underwater vehicle in the vertical plane. First, a new state-space representation for the vehicle dynamics is presented, and the corresponding problem formulation is clearly stated. Next, the two-controller set-up using a H ' -loop shaping design is employed to deal with the bottom following capability and robustness issues. Then the reduced order control system with a Hankel norm is evaluated in the frequency domain. In addition, the preview control approach is used to improve the overall tracking performance for undersea manoeuvres. The specific control tasks include the tracking of a set of depth profiles or ocean floors. Simulation results show that control objectives are effectively accomplished in spite of model uncertainties. Finally, it is found that the proposed control methodology is suitable for the depth trajectory following applications over a wide range of operating conditions.
Robust Control Application To Ciscrea Underwater Vehicle
Autonomous Underwater Vehicle (AUV) is an important marine observing platform for the sustainable use of ocean resources. In order to improve AUV motion performance for better observation quality, modeling and control issues should be addressed simultaneously. Currently, widely used Proportional Integral Derivative (PID) regulation is less efficient to handle parametric and dynamic uncertainties, as well as nonlinear hy-drodynamic damping effect. To address uncertain and nonlinear issues, we synthesized a model-based robust controller using H∞ approach. Without loss of generality, a robust heading controller for Ciscrea underwater vehicles is implemented. Simulations were conducted using our Computational Fluid Dynamic (CFD) numerical model. In our simulations, we considered a simple scenario using only one compass as heading feedback sensor, which is important for deep sea operation. Finally, robust yaw control results are compared with PID approach.