In this work, we design a nonlinear controller for an autonomous unmanned aerial vehicle (UAV) to follow a predefined trajectory. The UAV is made to follow the desired path by driving the UAV’s relative distance to t...
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In this work, we design a nonlinear controller for an autonomous unmanned aerial vehicle (UAV) to follow a predefined trajectory. The UAV is made to follow the desired path by driving the UAV’s relative distance to the path, and its look angle to zero. The proposed design is easy to implement as it does not need path curvature information and uses the philosophy of target pursuit to follow the predefined path. We further demonstrate the merits of the proposed method through simulations for various cases in accurately tracking straight line and curvilinear paths.
This paper studies the formation control of multiple quadrotor unmanned aerial vehicle systems (MQUAVSs) with external disturbance. A new adaptive fixed-time cooperative control protocol is designed for MQUAVSs. A fix...
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In this paper, a nonlinear impact time constrained three-dimensional guidance strategy to intercept a stationary target is proposed. The guidance strategy is based on non-singular terminal sliding mode control that us...
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In this paper, a nonlinear impact time constrained three-dimensional guidance strategy to intercept a stationary target is proposed. The guidance strategy is based on non-singular terminal sliding mode control that uses an improved time-to-go estimate in the design process, thereby provisioning for the interceptor’s large heading angle errors. Unlike existing approaches in the literature of three-dimensional terminal guidance, the proposed technique does not decouple the nonlinear three-dimensional engagement kinematics to design the guidance commands. Additionally, the proposed technique also considers the effect of autopilot whose dynamics are usually ignored. The stability of the proposed guidance strategy is certified using Lyapunov stability theory. Simulation results show the effective performance of the proposed guidance commands for various engagement conditions. The results in this paper are further backed with a comparison with an existing strategy that vindicates the superior performance of the proposed strategy.
As a novel computing paradigm, the Vehicular Edge Computing (VEC) network provides an additional avenue for onboard task execution for connected and automated vehicles (CAVs) in unmanned systems. In a VEC network, CAV...
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A guidance strategy is proposed in this paper that ensures near-zero miss distance along with simultaneous control over the direction and time of impact. The line-of-sight angle between the interceptor and the target ...
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A guidance strategy is proposed in this paper that ensures near-zero miss distance along with simultaneous control over the direction and time of impact. The line-of-sight angle between the interceptor and the target is shaped as a nonlinear polynomial function of relative range between them. This polynomial function provides the desired line-of-sight orientations to achieve the mission objectives. The coefficients of the line-of-sight polynomial are obtained by subjecting it to the boundary conditions that adhere to the desired terminal constraints. A controller is designed using the nonlinear dynamic inversion control technique to track the reference flight path directions derived using the desired line-of-sight orientations. The simulation results obtained from various numerical simulations validate the efficacy of the proposed guidance law.
In this paper, a sliding mode control-based cooperative guidance strategy for a team of two unmanned aerial vehicles (aircraft), which ensures their survival against pursuers, is proposed. The pursuing interceptors ar...
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In this paper, a sliding mode control-based cooperative guidance strategy for a team of two unmanned aerial vehicles (aircraft), which ensures their survival against pursuers, is proposed. The pursuing interceptors are assumed to employ augmented proportional navigation guidance. The cooperating aircraft maneuver in a way to lure their respective pursuers to an impact angle constrained collision. The problem of controlling impact angle is first transformed to that of tracking line-of-sight angle and its rate, and then the same is achieved by enforcing sliding mode on appropriate chosen switching surface. Furthermore, the allocation of aircraft’s lateral accelerations is performed in a way to minimize the instantaneous aerodynamic drag acting on both unmanned aerial vehicles. Numerical simulations are presented to validate the effectiveness of the proposed guidance strategy under different engagement geometries.
This paper addresses cooperative guidance for multiple interceptors targeting fast-moving non-accelerating targets. It proposes a strategy using arbitrary time consensus to establish unanimous agreement on interceptor...
This paper addresses cooperative guidance for multiple interceptors targeting fast-moving non-accelerating targets. It proposes a strategy using arbitrary time consensus to establish unanimous agreement on interceptors' time-to-go values early on. This parameter is crucial for successful simultaneous target interception. The paper introduces two salvo guidance strategies based on deviated pursuit and true proportional navigation (TPN), which are modified using a definitive consensus protocol to achieve consensus on time-to-go values. By integrating this consensus mechanism into the guidance laws, interceptors can maneuver to adjust trajectories to rendezvous with targets. The paper also emphasizes collab.rative decision-making through neighbor-to-neighbor communication to enhance overall guidance performance. Extensive numerical simulations validate the proposed approach, high-lighting its ability to achieve simultaneous target interception consistently and emphasizing the importance of cooperative time-constrained guidance for successful mission outcomes.
Human operator behavior in manual control of any electro-mechanical system can be complex and varied. It is possible to single out human operator behavior well described by linear differential equations. It allows for...
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Neurodegenerative disease especially dementia are reported as disease that leads to death, Alzheimer's Disease (AD) is kind dementia that cause progressive and irreversible brain disorder loss which leads to death...
Neurodegenerative disease especially dementia are reported as disease that leads to death, Alzheimer's Disease (AD) is kind dementia that cause progressive and irreversible brain disorder loss which leads to death. AD shows no symptoms in its early stages which makes diagnosing it its beginning a challenge and helpful for doctors as they can slow down its progress in its early stages. Computer-aided approaches such as machine learning which come up with several techniques to detect AD by extracting features from the given image data and use them to build a classifier. Recently, a subcategory of machine learning called deep learning has widely been employed to enhance the medical diagnosis by attempting notable performance. In fact, these approaches avoid the tricky manual feature extraction using Convolutional Neural Network (CNN) considered as a reference in the field of computer vision. This paper proposes a combination of machine-deep learning technics for early diagnosis of AD from positron emission tomography (PET). We first train our CNN on PET images to extract the most relevant features, then we select the most appropriate CNN's level from where the features will be extracted, which will be feed in a second step as input to a Support Vector Machine based classifier (SVM). The proposed approach achieves notable results that exceeded the performance obtained by various existing approaches.
Urban rail transit (URT) is vulnerable to natural disasters and social emergencies including fire, storm and epidemic (such as COVID-19), and real-time origin-destination (OD) flow prediction provides URT operators wi...
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