1,430 research outputs found

    Defense and Tolerance Technique Against Attacks and Faults on Leader-Following Multi-USVs

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    This study explores the leader-following consensus tracking control issue of multiple unmanned surface vehicles (multi-USVs) in the presence of malicious connectivity-mixed attacks in the cyber layer, and concurrent output channel noises, sensor/actuator faults, and wave-induced disturbances in the physical layer. Sensor/actuator faults are initially modeled with unified incipient and abrupt features. Additionally, connectivity-mixed attacks are depicted using connectivity-paralyzed and connectivity-maintained topologies through nonoverlapping and switching iterations. The standardization and observer design in multi-USVs are incorporated to decouple the augmented dynamics and estimate unknown state, fault, and noise observations, and then a defense and fault-tolerant consensus tracking control approach is designed to accomplish the robustness to disturbances/noises, resilience to attacks, and tolerance to faults, simultaneously. The criteria for achieving leader-following exponential consensus tracking of multi-USVs with cyber-physical threats can be determined based on activation rate and attack frequency indicators. Comparative simulations outline the effectiveness and economy of the proposed defense and tolerance technique against sensor/actuator faults and cyber-attacks on multi-USVs

    Mini Actuators for Safety Critical Unmanned Aerial Vehicles Avionics

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    The present article details the development steps and experimental results obtained during the development of smart actuators used on mini unmanned aerial vehicles (UAV). The research effort is driven by the need of developing onboard health monitoring and diagnostics units for small size UAVs to improve their reliability. In the present all small UAVs use single string avionics systems with no built in redundancy, moreover the servo actuators onboard the airplane are often commercial off the shelf (COTS) hobby components with no reliability figures, limited performance guarantees and one directional communication using analog PWM signals. The development of new servo generation focused on solving the above issues. The proposed servo actuators use the existing mechanical gearboxes and housing of the COTS components, but their power electronics, motor control hardware and software components, sensors are custom designed to fit the needs of a higher demand. The actuators with their controlling microprocessors are capable of establishing two way communication via CAN and FlexRay protocol, suitable for safety critical applications, and self diagnostics features are also hosted onboard the actuators. The development challenges and experimental results in a hardware-in-the-loop (HIL) simulator are discussed in the paper

    Fault Diagnosis and Fault Handling for Autonomous Aircraft

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    Fault Diagnosis and Fault-Tolerant Control of Unmanned Aerial Vehicles

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    With the increasing demand for unmanned aerial vehicles (UAVs) in both military and civilian applications, critical safety issues need to be specially considered in order to make better and wider use of them. UAVs are usually employed to work in hazardous and complex environments, which may seriously threaten the safety and reliability of UAVs. Therefore, the safety and reliability of UAVs are becoming imperative for development of advanced intelligent control systems. The key challenge now is the lack of fully autonomous and reliable control techniques in face of different operation conditions and sophisticated environments. Further development of unmanned aerial vehicle (UAV) control systems is required to be reliable in the presence of system component faults and to be insensitive to model uncertainties and external environmental disturbances. This thesis research aims to design and develop novel control schemes for UAVs with consideration of all the factors that may threaten their safety and reliability. A novel adaptive sliding mode control (SMC) strategy is proposed to accommodate model uncertainties and actuator faults for an unmanned quadrotor helicopter. Compared with the existing adaptive SMC strategies in the literature, the proposed adaptive scheme can tolerate larger actuator faults without stimulating control chattering due to the use of adaptation parameters in both continuous and discontinuous control parts. Furthermore, a fuzzy logic-based boundary layer and a nonlinear disturbance observer are synthesized to further improve the capability of the designed control scheme for tolerating model uncertainties, actuator faults, and unknown external disturbances while preventing overestimation of the adaptive control parameters and suppressing the control chattering effect. Then, a cost-effective fault estimation scheme with a parallel bank of recurrent neural networks (RNNs) is proposed to accurately estimate actuator fault magnitude and an active fault-tolerant control (FTC) framework is established for a closed-loop quadrotor helicopter system. Finally, a reconfigurable control allocation approach is combined with adaptive SMC to achieve the capability of tolerating complete actuator failures with application to a modified octorotor helicopter. The significance of this proposed control scheme is that the stability of the closed-loop system is theoretically guaranteed in the presence of both single and simultaneous actuator faults

    Event and Time-Triggered Control Module Layers for Individual Robot Control Architectures of Unmanned Agricultural Ground Vehicles

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    Automation in the agriculture sector has increased to an extent where the accompanying methods for unmanned field management are becoming more economically viable. This manifests in the industry’s recent presentation of conceptual cab-less machines that perform all field operations under the high-level task control of a single remote operator. A dramatic change in the overall workflow for field tasks that historically assumed the presence of a human in the immediate vicinity of the work is predicted. This shift in the entire approach to farm machinery work provides producers increased control and productivity over high-level tasks and less distraction from operating individual machine actuators and implements. The final implication is decreased mechanical complexity of the cab-less field machines from their manned counter types. An Unmanned Agricultural Ground Vehicle (UAGV) electric platform received a portable control module layer (CML) which was modular and able to accept higher-level mission commands while returning system states to high-level tasks. The simplicity of this system was shown by its entire implementation running on microcontrollers networked on a Time-Triggered Controller Area Network (TTCAN) bus. A basic form of user input and output was added to the system to demonstrate a simple instance of sub-system integration. In this work, all major levels of design and implementation are examined in detail, revealing the ‘why’ and ‘how’ of each subsystem. System design philosophy is highlighted from the beginning. A state-space feedback steering controller was implemented on the machine utilizing a basic steering model found in literature. Finally, system performance is evaluated from the perspectives of a number of disciplines including: embedded systems software design, control systems, and robot control architecture. Recommendations for formalized UAGV system modeling, estimation, and control are discussed for the continuation of research in simplified low-cost machines for in-field task automation. Additional recommendations for future time-triggered CML experiments in bus robustness and redundancy are discussed. The work presented is foundational in the shift from event-triggered communications towards time-triggered CMLs for unmanned agricultural machinery and is a front-to-back demonstration of time-triggered design. Advisor: Santosh K. Pitl

    Feasible, Robust and Reliable Automation and Control for Autonomous Systems

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    The Special Issue book focuses on highlighting current research and developments in the automation and control field for autonomous systems as well as showcasing state-of-the-art control strategy approaches for autonomous platforms. The book is co-edited by distinguished international control system experts currently based in Sweden, the United States of America, and the United Kingdom, with contributions from reputable researchers from China, Austria, France, the United States of America, Poland, and Hungary, among many others. The editors believe the ten articles published within this Special Issue will be highly appealing to control-systems-related researchers in applications typified in the fields of ground, aerial, maritime vehicles, and robotics as well as industrial audiences

    Integrated fault-tolerant control approach for linear time-delay systems using a dynamic event-triggered mechanism

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    In this study, a novel integrated fault estimation (FE) and fault-tolerant control (FTC) design approach is developed for a system with time-varying delays and additive fault based on a dynamic event-triggered communication mechanism. The traditional static event-triggered mechanism is modified by adding an internal dynamic variable to increase the inter-event interval and decrease the amount of data transmission. Then, a dynamical observer is designed to estimate both the system state and the unknown fault signal simultaneously. A fault estimation-based FTC approach is then given to remove the effects generated by unknown actuator faults, which guarantees that the faulty closed-loop systems are asymptotical stable with a disturbance attenuation level γ. By theory analysis, the Zeno phenomenon is excluded in this study. Finally, a real aircraft engine example is provided to illustrate the feasibility of the proposed integrated FE and FTC method

    Avionics-based GNSS integrity augmentation for unmanned aerial systems sense-and-avoid

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    This paper investigates the synergies between a GNSS Avionics Based Integrity Augmentation (ABIA) system and a novel Unmanned Aerial System (UAS) Sense-and-Avoid (SAA) architecture for cooperative and non-cooperative scenarios. The integration of ABIA with SAA has the potential to provide an integrity-augmented SAA solution that will allow the safe and unrestricted access of UAS to commercial airspace. The candidate SAA system uses Forward-Looking Sensors (FLS) for the non-cooperative case and Automatic Dependent Surveillance-Broadcast (ADS-B) for the cooperative case. In the non-cooperative scenario, the system employs navigation-based image stabilization with image morphology operations and a multi-branch Viterbi filter for obstacle detection, which allows heading estimation. The system utilizes a Track-to-Track (T3) algorithm for data fusion that allows combining data from different tracks obtained with FLS and/or ADS-B depending on the scenario. Successively, it utilizes an Interacting Multiple Model (IMM) algorithm to estimate the state vector allowing a prediction of the intruder trajectory over a specified time horizon. Both in the cooperative and non-cooperative cases, the risk of collision is evaluated by setting a threshold on the Probability Density Function (PDF) of a Near Mid-Air Collision (NMAC) event over the separation area. So, if the specified threshold is exceeded, an avoidance manoeuver is performed based on a heading-based Differential Geometry (DG) algorithm and optimized utilizing a cost function with minimum time constraints and fuel penalty criteria weighted as a function of separation distance. Additionally, the optimised avoidance trajectory considers the constraints imposed by the ABIA in terms of GNSS constellation satellite elevation angles, preventing degradation or losses of navigation data during the whole SAA loop. This integration scheme allows real-time trajectory corrections to re-establish the Required Navigation Performance (RNP) when actual GNSS accuracy degradations and/or data losses take place (e.g., due to aircraft-satellite relative geometry, GNSS receiver tracking, interference, jamming or other external factors). Various simulation case studies were accomplished to evaluate the performance of this Integrity-Augmented SAA (IAS) architecture. The selected host platform was the AEROSONDE Unmanned Aerial Vehicle (UAV) and the simulation cases addressed a variety of cooperative and non-cooperative scenarios in a representative cross-section of the AEROSONDE operational flight envelope. The simulation results show that the proposed IAS architecture is an excellent candidate to perform high-integrity Collision Detection and Resolution (CD&R) utilizing GNSS as the primary source of navigation data, providing solid foundation for future research and developments in this domain

    Avionics-based GNSS integrity augmentation for unmanned aerial systems sense-and-avoid

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    This paper investigates the synergies between a GNSS Avionics Based Integrity Augmentation (ABIA) system and a novel Unmanned Aerial System (UAS) Sense-and-Avoid (SAA) architecture for cooperative and non-cooperative scenarios. The integration of ABIA with SAA has the potential to provide an integrity-augmented SAA solution that will allow the safe and unrestricted access of UAS to commercial airspace. The candidate SAA system uses Forward-Looking Sensors (FLS) for the non-cooperative case and Automatic Dependent Surveillance-Broadcast (ADS-B) for the cooperative case. In the non-cooperative scenario, the system employs navigation-based image stabilization with image morphology operations and a multi-branch Viterbi filter for obstacle detection, which allows heading estimation. The system utilizes a Track-to-Track (T3) algorithm for data fusion that allows combining data from different tracks obtained with FLS and/or ADS-B depending on the scenario. Successively, it utilizes an Interacting Multiple Model (IMM) algorithm to estimate the state vector allowing a prediction of the intruder trajectory over a specified time horizon. Both in the cooperative and non-cooperative cases, the risk of collision is evaluated by setting a threshold on the Probability Density Function (PDF) of a Near Mid-Air Collision (NMAC) event over the separation area. So, if the specified threshold is exceeded, an avoidance manoeuver is performed based on a heading-based Differential Geometry (DG) algorithm and optimized utilizing a cost function with minimum time constraints and fuel penalty criteria weighted as a function of separation distance. Additionally, the optimised avoidance trajectory considers the constraints imposed by the ABIA in terms of GNSS constellation satellite elevation angles, preventing degradation or losses of navigation data during the whole SAA loop. This integration scheme allows real-time trajectory corrections to re-establish the Required Navigation Performance (RNP) when actual GNSS accuracy degradations and/or data losses take place (e.g., due to aircraft-satellite relative geometry, GNSS receiver tracking, interference, jamming or other external factors). Various simulation case studies were accomplished to evaluate the performance of this Integrity-Augmented SAA (IAS) architecture. The selected host platform was the AEROSONDE Unmanned Aerial Vehicle (UAV) and the simulation cases addressed a variety of cooperative and non-cooperative scenarios in a representative cross-section of the AEROSONDE operational flight envelope. The simulation results show that the proposed IAS architecture is an excellent candidate to perform high-integrity Collision Detection and Resolution (CD&R) utilizing GNSS as the primary source of navigation data, providing solid foundation for future research and developments in this domain
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