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Didik Soetanto

Bio: Didik Soetanto is an academic researcher. The author has contributed to research in topics: Trajectory & Control system. The author has an hindex of 1, co-authored 1 publications receiving 281 citations.

Papers
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Journal ArticleDOI
TL;DR: In this paper, a nonlinear feedback control law is developed to steer an AUV along a desired path, which overcomes initial condition constraints that are present in a number of path-following control strategies described in the literature.

314 citations


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BookDOI
08 Apr 2011
TL;DR: In this article, the authors present a survey of the latest tools for analysis and design of advanced guidance, navigation and control systems and present new material on underwater vehicles and surface vessels.
Abstract: The technology of hydrodynamic modeling and marine craft motion control systems has progressed greatly in recent years. This timely survey includes the latest tools for analysis and design of advanced guidance, navigation and control systems and presents new material on underwater vehicles and surface vessels. Each section presents numerous case studies and applications, providing a practical understanding of how model-based motion control systems are designed.

1,389 citations

Journal ArticleDOI
TL;DR: In this article, a leader-follower formation control of multiple underactuated autonomous underwater vehicles (AUVs) is proposed, where the follower tracks a reference trajectory based on the leader position and predetermined formation without the need for leader's velocity and dynamics.

566 citations

Journal ArticleDOI
TL;DR: Simulation results substantiate the efficacy of the proposed method for output-feedback path-following of under-actuated autonomous underwater vehicles and prove that all error signals in the closed-loop system are uniformly and ultimately bounded.
Abstract: This paper presents a design method for output-feedback path-following control of under-actuated autonomous underwater vehicles moving in a vertical plane without using surge, heave, and pitch velocities. Specifically, an extended state observer (ESO) is developed to recover the unmeasured velocities as well as to estimate total uncertainty induced by internal model uncertainty and external disturbance. At the kinematic level, a commanded guidance law is developed based on a vertical line-of-sight guidance scheme and the observed velocities. To optimize guidance signals, optimization-based reference governors are formulated as bound-constrained quadratic programming problems for computing optimal reference signals. Two globally convergent recurrent neural networks called projection neural networks are used to solve the optimization problems in real-time. Based on the optimal reference signals and ESO, a kinetic control law with disturbance rejection capability is constructed at the kinetic level. It is proved that all error signals in the closed-loop system are uniformly and ultimately bounded. Simulation results substantiate the efficacy of the proposed method for output-feedback path-following of under-actuated autonomous underwater vehicles.

281 citations

Journal ArticleDOI
TL;DR: The design and analysis process of direct/indirect adaptive fuzzy control and fuzzy PID control in marine robotic fields are summarized and trends of the fuzzy future in Marine robotic vehicles are concluded based on its state of the art.
Abstract: Fuzzy logic control, due to its simple control structure, easy and cost-effective design, has been successfully employed to the application of guidance and control in robotic fields. This paper aims to review fuzzy-logic-based guidance and control in an important branch of robots—marine robotic vehicles. First, guidance and motion forms including the maneuvering, path following, trajectory tracking, and position stabilization are described. Subsequently, the application of three major classes of fuzzy logic control, including the conventional fuzzy control (Mamdani fuzzy control and Takagi–Sugeno–Kang fuzzy control), adaptive fuzzy control (self-tuning fuzzy control and direct/indirect adaptive fuzzy control), and hybrid fuzzy control (fuzzy PID control, fuzzy sliding mode control, and neuro-fuzzy control) are presented. In particular, we summarize the design and analysis process of direct/indirect adaptive fuzzy control and fuzzy PID control in marine robotic fields. In addition, two comparative results between hybrid fuzzy control and the corresponding single control are provided to illustrate the superiority of hybrid fuzzy control. Finally, trends of the fuzzy future in marine robotic vehicles are concluded based on its state of the art.

263 citations

Journal ArticleDOI
TL;DR: Against most existing methods for 3D path following, the proposed robust fuzzy control scheme reduces the design and implementation costs of complicated dynamics controller, and relaxes the knowledge of the accuracy dynamics modelling and environmental disturbances.

234 citations