83 research outputs found
Distributed Neurodynamics-Based Backstepping Optimal Control for Robust Constrained Consensus of Underactuated Underwater Vehicles Fleet
Robust constrained formation tracking control of underactuated underwater
vehicles (UUVs) fleet in three-dimensional space is a challenging but practical
problem. To address this problem, this paper develops a novel consensus based
optimal coordination protocol and a robust controller, which adopts a
hierarchical architecture. On the top layer, the spherical coordinate transform
is introduced to tackle the nonholonomic constraint, and then a distributed
optimal motion coordination strategy is developed. As a result, the optimal
formation tracking of UUVs fleet can be achieved, and the constraints are
fulfilled. To realize the generated optimal commands better and, meanwhile,
deal with the underactuation, at the lower-level control loop a neurodynamics
based robust backstepping controller is designed, and in particular, the issue
of "explosion of terms" appearing in conventional backstepping based
controllers is avoided and control activities are improved. The stability of
the overall UUVs formation system is established to ensure that all the states
of the UUVs are uniformly ultimately bounded in the presence of unknown
disturbances. Finally, extensive simulation comparisons are made to illustrate
the superiority and effectiveness of the derived optimal formation tracking
protocol.Comment: This paper is accepted by IEEE Transactions on Cybernetic
Formation Control and Fault Accommodation for a Team of Autonomous Underwater Vehicles
The purpose of this thesis is the development of efficient formation control and fault accommodation algorithms for a team of autonomous underwater vehicles (AUVs). The team of AUVs are capable of performing a wide range of deep water marine applications such as seabed mapping and surveying, oil and gas exploration and extraction, and oil and gas pipeline inspection. However, communication limitations and the presence of undesirable events such as component faults in any of the team members can prevent the whole team to achieve safe, reliable, and efficient performance while executing underwater mission tasks.
In this regard, the semi-decentralized control scheme is developed to achieve trajectory tracking and formation keeping while requiring information exchange only among neighboring agents. To this end, model predictive control (MPC) technique
and dynamic game theory are utilized to formulate and solve the formation control problem. Moreover, centralized and decentralized control schemes are developed to assess the performance of the proposed semi-decentralized control scheme in the simulation studies. The simulation results verify that the performance of the proposed semi-decentralized scheme is very close to the centralized scheme with lower control effort cost while it does not impose stringent communication requirements as in the centralized scheme.
Moreover, the semi-decentralized active fault recovery scheme is developed to maintain a graceful degraded performance and to ensure that the team of autonomous underwater vehicles can satisfy mission objectives when an actuator fault occurs in
any of the team members. In this regard, online fault information provided by fault detection and isolation (FDI) modules of each agent and its neighbors are incorporated to redesign the nominal controllers based on the MPC technique and dynamic game theory. Additionally, FDI imperfections such as fault estimation error and time delay are taken into account, and a performance index is derived to show the impact of FDI imperfections on the performance of team members. Moreover, centralized and decentralized active fault recovery schemes are developed to evaluate the performance of the proposed semi-decentralized recovery scheme through comparative simulation studies with various fault scenarios. The comparative simulation studies justify that the proposed semi-decentralized fault recovery scheme meets the design specifications even if the performance of the FDI module is not ideal
Optimal Time-Invariant Distributed Formation Tracking for Second-Order Multi-Agent Systems
This paper addresses the optimal time-invariant formation tracking problem
with the aim of providing a distributed solution for multi-agent systems with
second-order integrator dynamics. In the literature, most of the results
related to multi-agent formation tracking do not consider energy issues while
investigating distributed feedback control laws. In order to account for this
crucial design aspect, we contribute by formalizing and proposing a solution to
an optimization problem that encapsulates trajectory tracking, distance-based
formation control, and input energy minimization, through a specific and key
choice of potential functions in the optimization cost. To this end, we show
how to compute the inverse dynamics in a centralized fashion by means of the
Projector-Operator-based Newton's method for Trajectory Optimization (PRONTO)
and, more importantly, we exploit such an offline solution as a general
reference to devise a novel online distributed control law. Finally, numerical
examples involving a cubic formation following a straight path in the 3D space
are provided to validate the proposed control strategies.Comment: 28 pages, 2 figures, submitted to the European Journal of Control on
June 23rd, 2023 (version 1
Distributed MPC for Formation Path-Following of Multi-Vehicle Systems
The paper considers the problem of formation path-following of multiple vehicles and proposes a solution based on combining distributed model predictive control with parametrizations of the trajectories of the vehicles using polynomial splines. Introducing such parametrization leads indeed to two potential benefits: A) reducing the number of optimization variables, and b) enabling enforcing constraints on the vehicles in a computationally efficient way. Moreover, the proposed solution formulates the formation path-following problem as a distributed optimization problem that may then be solved using the alternating direction method of multipliers (ADMM). The paper then analyzes the effectiveness of the proposed method via numerical simulations with surface vehicles and differential drive robotspublishedVersio
A survey of formation control and motion planning of multiple unmanned vehicles
The increasing deployment of multiple unmanned vehicles systems has generated large research interest in recent decades. This paper therefore provides a detailed survey to review a range of techniques related to the operation of multi-vehicle systems in different environmental domains, including land based, aerospace and marine with the specific focuses placed on formation control and cooperative motion planning. Differing from other related papers, this paper pays a special attention to the collision avoidance problem and specifically discusses and reviews those methods that adopt flexible formation shape to achieve collision avoidance for multi-vehicle systems. In the conclusions, some open research areas with suggested technologies have been proposed to facilitate the future research development
Development of Path Following and Cooperative Motion Control Algorithms for Autonomous Underwater Vehicles
Research on autonomous underwater vehicle (AUV) is motivating and challenging owing to their specific applications such as defence, mine counter measure, pipeline inspections, risky missions e.g. oceanographic observations, bathymetric surveys, ocean floor analysis, military uses, and recovery of lost man-made objects. Motion control of AUVs is concerned with navigation, path following and co-operative motion control problems.
A number of control complexities are encountered in AUV motion control such as nonlinearities in mass matrix, hydrodynamic terms and ocean currents. These pose challenges to develop efficient control algorithms such that the accurate path following task and effective group co-ordination can be achieved in face of parametric uncertainties and disturbances and communication constraints in acoustic medium. This thesis first proposes development of a number of path following control laws and new co-operative motion control algorithms for achieving successful motion control objectives. These algorithms are potential function based proportional derivative path following control laws, adaptive trajectory based formation control, formation control of multiple AUVs steering towards a safety region, mathematical potential function based flocking control and fuzzy potential function based flocking control. Development of a path following control algorithm aims at generating appropriate control law, such that an AUV tracks a predefined desired path. In this thesis first path following control laws are developed for an underactuated (the number of inputs are lesser than the degrees of freedom) AUV. A potential function based proportional derivative (PFPD) control law is derived to govern the motion of the AUV in an obstacle-rich environment (environment populated by obstacles). For obstacle avoidance, a mathematical potential function is exploited, which provides a repulsive force between the AUV and the solid obstacles intersecting the desired path. Simulations were carried out considering a special type of AUV i.e. Omni Directional Intelligent Navigator (ODIN) to study the efficacy of the developed PFPD controller. For achieving more accuracy in the path following performance, a new controller (potential function based augmented proportional derivative, PFAPD) has been designed by the mass matrix augmentation with PFPD control law. Simulations were made and the results obtained with PFAPD controller are compared with that of PFPD controlle
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