291 research outputs found

    3D Coordinated Path Following with Disturbance Rejection for Formations of Under-actuated Agents

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    In this paper coordinated path following for formations of under-actuated agents in three dimensional space is considered. The agents are controlled to follow a straight-line path whilst being affected by an unknown environmental disturbance. The problem is solved using a twofold approach. In particular, the agents are controlled to the desired path using a guidance law that rejects an unknown, but constant, disturbance. Simultaneously each agent utilises a decentralised nonlinear coordination law to achieve the desired formation. The closed-loop system of path-following and coordination dynamics is analysed using theory for feedback-interconnected systems. In particular, a technique from [1] is used that allows us to analyse a feedback-interconnected systems as a cascaded system. The origin of the closed-loop error dynamics is shown to be globally asymptotically stable. A case study with simulation results is presented to validate the control strategy.(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works

    Underactuated leader-follower synchronisation for multi-agent systems with rejection of unknown disturbances

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    Author preprintIn this paper leader-follower synchronization is considered for underactuated followers in an inhomogeneous multi-agent system. The goal is to synchronise the motion of a leader and an underactuated follower. Measurements of the leader's position and velocity are available, while the dynamics and trajectory of the leader is unknown. The leader velocities are used as input for a constant bearing guidance algorithm to assure that the follower synchronises its motion to the leader. It is also shown that the proposed leader-follower scheme can be applied to multi-agent systems that are subjected to unknown environmental disturbances. Furthermore, the trajectory of the leader does not need to be known. The stability properties of the complete control scheme and the unactuated internal dynamics are analysed using nonlinear cascaded system theory. Simulation results are presented to validate the proposed control strategy.Preprint version. © IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works

    Data-Driven Architecture to Increase Resilience In Multi-Agent Coordinated Missions

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    The rise in the use of Multi-Agent Systems (MASs) in unpredictable and changing environments has created the need for intelligent algorithms to increase their autonomy, safety and performance in the event of disturbances and threats. MASs are attractive for their flexibility, which also makes them prone to threats that may result from hardware failures (actuators, sensors, onboard computer, power source) and operational abnormal conditions (weather, GPS denied location, cyber-attacks). This dissertation presents research on a bio-inspired approach for resilience augmentation in MASs in the presence of disturbances and threats such as communication link and stealthy zero-dynamics attacks. An adaptive bio-inspired architecture is developed for distributed consensus algorithms to increase fault-tolerance in a network of multiple high-order nonlinear systems under directed fixed topologies. In similarity with the natural organisms’ ability to recognize and remember specific pathogens to generate its immunity, the immunity-based architecture consists of a Distributed Model-Reference Adaptive Control (DMRAC) with an Artificial Immune System (AIS) adaptation law integrated within a consensus protocol. Feedback linearization is used to modify the high-order nonlinear model into four decoupled linear subsystems. A stability proof of the adaptation law is conducted using Lyapunov methods and Jordan decomposition. The DMRAC is proven to be stable in the presence of external time-varying bounded disturbances and the tracking error trajectories are shown to be bounded. The effectiveness of the proposed architecture is examined through numerical simulations. The proposed controller successfully ensures that consensus is achieved among all agents while the adaptive law v simultaneously rejects the disturbances in the agent and its neighbors. The architecture also includes a health management system to detect faulty agents within the global network. Further numerical simulations successfully test and show that the Global Health Monitoring (GHM) does effectively detect faults within the network

    Adaptive and Optimal Motion Control of Multi-UAV Systems

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    This thesis studies trajectory tracking and coordination control problems for single and multi unmanned aerial vehicle (UAV) systems. These control problems are addressed for both quadrotor and fixed-wing UAV cases. Despite the fact that the literature has some approaches for both problems, most of the previous studies have implementation challenges on real-time systems. In this thesis, we use a hierarchical modular approach where the high-level coordination and formation control tasks are separated from low-level individual UAV motion control tasks. This separation helps efficient and systematic optimal control synthesis robust to effects of nonlinearities, uncertainties and external disturbances at both levels, independently. The modular two-level control structure is convenient in extending single-UAV motion control design to coordination control of multi-UAV systems. Therefore, we examine single quadrotor UAV trajectory tracking problems to develop advanced controllers compensating effects of nonlinearities and uncertainties, and improving robustness and optimality for tracking performance. At fi rst, a novel adaptive linear quadratic tracking (ALQT) scheme is developed for stabilization and optimal attitude control of the quadrotor UAV system. In the implementation, the proposed scheme is integrated with Kalman based reliable attitude estimators, which compensate measurement noises. Next, in order to guarantee prescribed transient and steady-state tracking performances, we have designed a novel backstepping based adaptive controller that is robust to effects of underactuated dynamics, nonlinearities and model uncertainties, e.g., inertial and rotational drag uncertainties. The tracking performance is guaranteed to utilize a prescribed performance bound (PPB) based error transformation. In the coordination control of multi-UAV systems, following the two-level control structure, at high-level, we design a distributed hierarchical (leader-follower) 3D formation control scheme. Then, the low-level control design is based on the optimal and adaptive control designs performed for each quadrotor UAV separately. As particular approaches, we design an adaptive mixing controller (AMC) to improve robustness to varying parametric uncertainties and an adaptive linear quadratic controller (ALQC). Lastly, for planar motion, especially for constant altitude flight of fixed-wing UAVs, in 2D, a distributed hierarchical (leader-follower) formation control scheme at the high-level and a linear quadratic tracking (LQT) scheme at the low-level are developed for tracking and formation control problems of the fixed-wing UAV systems to examine the non-holonomic motion case. The proposed control methods are tested via simulations and experiments on a multi-quadrotor UAV system testbed

    Top-Down & Bottom-Up Approaches to Robot Design

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    This thesis presents a study of different engineering design methodologies and demonstrates their effectiveness and limitations in actual robot designs. Some of these methods were blended together with focus on providing an easily interpreted project design flow while implementing more bottom-up, or feedback, elements into the design methodology. Typically design methods are learned through experience, and design taught in academia aims to shape and formalize previous experience. Usually, inexperienced engineers are taught approaches resembling the Verein Deutscher Ingenieure (VDI) 2221 process. This method presented by the Association of German Engineers in 2006 is regarded as the general system design process. This introductory process is largely left open to interpretation, and it is often unclear when to implement feedback in the design process. The objective of this thesis is to investigate the roles of top-down and bottom-up processes, and how to integrate them in the robot design methodology. The proposed approach utilizes several components from existing design methods. There are three main conditional loops within the proposed approach. The first loop focuses on defining the problem in a top-down manner through logical decomposition, defining technical requirements, researching solutions, and conducting a trade study. These four steps are done iteratively until reaching the bottom of the system, the most primitive components. This is followed by a modeling and analysis loop. This works from the bottom to the top of the design in preparation for manufacturing and validation. The final loop of the proposed approach focuses on validation and verification. The testing and manufacturing involved allows for alterations to the design to fulfill the original technical requirements. These three loops occur until a proof of concept is achieved. The proposed method is intended to be applied iteratively. The first pass of the method results in a proof of concept, while the second results in a preproduction prototype, and the third in a production model. This assembly of design elements provides a project flow that leaves little to be interpreted and is suitable for small design teams while still flexible enough to be applied to diverse robotics projects. This thesis provides three case studies analyzing the application of the hybrid design approach mentioned above to robotic system development. The first study showcases a complicated system design with a small development team. The second case is of simpler construction with a smaller developer team. This simpler case better demonstrates the benefits of this hybrid approach in robotic system development due to the comparatively higher speed at which the system matures. The third case study shows how this same proposed approach can be applied to the design of a bottom-up controlled swarm. These case studies are for future designers to reference as examples of the hybrid design methodology in application, and what can happen when there is a lack of feedback in design. This proposed hybrid design method can encourage design practices in new engineers that translate better to industrial applications, and therefore encourage faster integration of new engineers into established design engineering practices

    Development of Path Following and Cooperative Motion Control Algorithms for Autonomous Underwater Vehicles

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    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

    Multi-agent Collision Avoidance Using Interval Analysis and Symbolic Modelling with its Application to the Novel Polycopter

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    Coordination is fundamental component of autonomy when a system is defined by multiple mobile agents. For unmanned aerial systems (UAS), challenges originate from their low-level systems, such as their flight dynamics, which are often complex. The thesis begins by examining these low-level dynamics in an analysis of several well known UAS using a novel symbolic component-based framework. It is shown how this approach is used effectively to define key model and performance properties necessary of UAS trajectory control. This is demonstrated initially under the context of linear quadratic regulation (LQR) and model predictive control (MPC) of a quadcopter. The symbolic framework is later extended in the proposal of a novel UAS platform, referred to as the ``Polycopter" for its morphing nature. This dual-tilt axis system has unique authority over is thrust vector, in addition to an ability to actively augment its stability and aerodynamic characteristics. This presents several opportunities in exploitative control design. With an approach to low-level UAS modelling and control proposed, the focus of the thesis shifts to investigate the challenges associated with local trajectory generation for the purpose of multi-agent collision avoidance. This begins with a novel survey of the state-of-the-art geometric approaches with respect to performance, scalability and tolerance to uncertainty. From this survey, the interval avoidance (IA) method is proposed, to incorporate trajectory uncertainty in the geometric derivation of escape trajectories. The method is shown to be more effective in ensuring safe separation in several of the presented conditions, however performance is shown to deteriorate in denser conflicts. Finally, it is shown how by re-framing the IA problem, three dimensional (3D) collision avoidance is achieved. The novel 3D IA method is shown to out perform the original method in three conflict cases by maintaining separation under the effects of uncertainty and in scenarios with multiple obstacles. The performance, scalability and uncertainty tolerance of each presented method is then examined in a set of scenarios resembling typical coordinated UAS operations in an exhaustive Monte-Carlo analysis

    New decentralized algorithms for spacecraft formation control based on a cyclic approach

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 223-231).When considering the formation control problem for large number of spacecraft, the advantages of implementing control approaches with a centralized coordination mechanism can be outpaced by the risks associated with having a primary vital control unit. Additionally, in formations with a large number of spacecraft, a centralized approach implies an inherent difficulty in gathering and broadcasting information from/to the overall system. Therefore, there is a need to explore efficient decentralized control approaches. In this thesis a new approach to spacecraft formation control is formulated by exploring and enhancing the recent results on the theory of convergence to geometric patterns and exploring the analysis of this approach using the tools of contracting theory. First, an extensive analysis of the cyclic pursuit dynamics leads to developing control laws useful for spacecraft formation flight which, as opposed to the most common approaches in the literature, do not track fixed relative trajectories and therefore, reduce the global coordination requirements. The proposed approach leads to local control laws that verify global emergent behaviors specified as convergence to a particular manifold. A generalized analysis of such control approach by using tools of partial contraction theory is performed, producing important convergence results. By applying and extending results from the theory of partially contracting systems, an approach to deriving sufficient conditions for convergence is formulated. Its use is demonstrated by analyzing several examples and obtaining global convergence results for nonlinear, time varying and more complex interconnected distributed controllers. Experimental results of the implementation of these algorithms were obtained using the SPHERES testbed on board the International Space Station, validating many of the important properties of this decentralized control approach. They are believed to be the first implementation of decentralized formation flight in space. To complement the results we also consider a short analysis of the advantages of decentralized versus centralized approach by comparing the optimal performance and the effects of complexity and robustness for different architectures and address the issues of implementing decentralized algorithms in a inherently coupled system like the Electromagnetic Formation Flight.by Jaime Luís Ramírez Riberos.Ph.D

    Development of Robust Control Strategies for Autonomous Underwater Vehicles

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    The resources of the energy and chemical balance in the ocean sustain mankind in many ways. Therefore, ocean exploration is an essential task that is accomplished by deploying Underwater Vehicles. An Underwater Vehicle with autonomy feature for its navigation and control is called Autonomous Underwater Vehicle (AUV). Among the task handled by an AUV, accurately positioning itself at a desired position with respect to the reference objects is called set-point control. Similarly, tracking of the reference trajectory is also another important task. Battery recharging of AUV, positioning with respect to underwater structure, cable, seabed, tracking of reference trajectory with desired accuracy and speed to avoid collision with the guiding vehicle in the last phase of docking are some significant applications where an AUV needs to perform the above tasks. Parametric uncertainties in AUV dynamics and actuator torque limitation necessitate to design robust control algorithms to achieve motion control objectives in the face of uncertainties. Sliding Mode Controller (SMC), H / μ synthesis, model based PID group controllers are some of the robust controllers which have been applied to AUV. But SMC suffers from less efficient tuning of its switching gains due to model parameters and noisy estimated acceleration states appearing in its control law. In addition, demand of high control effort due to high frequency chattering is another drawback of SMC. Furthermore, real-time implementation of H / μ synthesis controller based on its stability study is restricted due to use of linearly approximated dynamic model of an AUV, which hinders achieving robustness. Moreover, model based PID group controllers suffer from implementation complexities and exhibit poor transient and steady-state performances under parametric uncertainties. On the other hand model free Linear PID (LPID) has inherent problem of narrow convergence region, i.e.it can not ensure convergence of large initial error to zero. Additionally, it suffers from integrator-wind-up and subsequent saturation of actuator during the occurrence of large initial error. But LPID controller has inherent capability to cope up with the uncertainties. In view of addressing the above said problem, this work proposes wind-up free Nonlinear PID with Bounded Integral (BI) and Bounded Derivative (BD) for set-point control and combination of continuous SMC with Nonlinear PID with BI and BD namely SM-N-PID with BI and BD for trajectory tracking. Nonlinear functions are used for all P,I and D controllers (for both of set-point and tracking control) in addition to use of nonlinear tan hyperbolic function in SMC(for tracking only) such that torque demand from the controller can be kept within a limit. A direct Lyapunov analysis is pursued to prove stable motion of AUV. The efficacies of the proposed controllers are compared with other two controllers namely PD and N-PID without BI and BD for set-point control and PD plus Feedforward Compensation (FC) and SM-NPID without BI and BD for tracking control. Multiple AUVs cooperatively performing a mission offers several advantages over a single AUV in a non-cooperative manner; such as reliability and increased work efficiency, etc. Bandwidth limitation in acoustic medium possess challenges in designing cooperative motion control algorithm for multiple AUVs owing to the necessity of communication of sensors and actuator signals among AUVs. In literature, undirected graph based approach is used for control design under communication constraints and thus it is not suitable for large number of AUVs participating in a cooperative motion plan. Formation control is a popular cooperative motion control paradigm. This thesis models the formation as a minimally persistent directed graph and proposes control schemes for maintaining the distance constraints during the course of motion of entire formation. For formation control each AUV uses Sliding Mode Nonlinear PID controller with Bounded Integrator and Bounded Derivative. Direct Lyapunov stability analysis in the framework of input-to-state stability ensures the stable motion of formation while maintaining the desired distance constraints among the AUVs

    Intelligent Escape of Robotic Systems: A Survey of Methodologies, Applications, and Challenges

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    Intelligent escape is an interdisciplinary field that employs artificial intelligence (AI) techniques to enable robots with the capacity to intelligently react to potential dangers in dynamic, intricate, and unpredictable scenarios. As the emphasis on safety becomes increasingly paramount and advancements in robotic technologies continue to advance, a wide range of intelligent escape methodologies has been developed in recent years. This paper presents a comprehensive survey of state-of-the-art research work on intelligent escape of robotic systems. Four main methods of intelligent escape are reviewed, including planning-based methodologies, partitioning-based methodologies, learning-based methodologies, and bio-inspired methodologies. The strengths and limitations of existing methods are summarized. In addition, potential applications of intelligent escape are discussed in various domains, such as search and rescue, evacuation, military security, and healthcare. In an effort to develop new approaches to intelligent escape, this survey identifies current research challenges and provides insights into future research trends in intelligent escape.Comment: This paper is accepted by Journal of Intelligent and Robotic System
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