Robust Guidance System for Maneuvering Targets

2021 ◽  
Author(s):  
Adel M. Soliman ◽  
Yasser M. Madany ◽  
Hesham A. Abdin ◽  
Ahmed F. Miligy
Keyword(s):  
Guidance System ◽  
Maneuvering Targets

Partial Stabilization Approach to 3-Dimensional Guidance Law Design

2011 ◽  
Vol 133 (6) ◽  
Author(s):  
T. Binazadeh ◽  
M. J. Yazdanpanah
Keyword(s):  
System Dynamics ◽  
The State ◽  
Guidance System ◽  
Missile Guidance ◽  
State Variables ◽  
New Approach ◽  
3 Dimensional ◽  
Guidance Law ◽  
Maneuvering Targets

In this paper, a new approach to design the 3-dimensional missile guidance law, based on partial stabilization, is presented. The approach is based on the classification of the state variables within the guidance system dynamics with respect to their required stabilization properties. The resulting guidance law enables the missile to intercept highly maneuvering targets within a finite interception time. Effectiveness of the proposed guidance law is demonstrated through analysis and simulations.

Fast fixed-time convergent smooth adaptive guidance law with terminal angle constraint for interception of maneuvering targets

2020 ◽  
pp. 095441002096509
Author(s):  
Peng Zhang ◽  
Xiaoyu Zhang
Keyword(s):  
Stability Theory ◽  
Sliding Mode ◽  
Fixed Time ◽  
Guidance System ◽  
Time Stability ◽  
Terminal Sliding Mode ◽  
Guidance Law ◽  
Maneuvering Targets ◽  
System States ◽  
Terminal Angle Constraint

This paper introduces a fast fixed-time guidance law with terminal angle constraint for interception of maneuvering targets, which is based on the structure of singularity-free fast terminal sliding mode and the fixed-time stability theory. Different from the finite-time stability, the fixed-time stability can predefine the maximum stabilization time of system states which is independent on the initial value of system states. Under the proposed guidance law, the guidance system can achieve stabilization within settling time which decides by the parameters of controller. In addition, an adaptive law is proposed which alleviate the chattering of sliding mode and smooths the guidance law. Meanwhile, the proof of the sliding mode manifold and system states fixed-time convergence is given by Lyapunov stability theory. Finally, numerical simulations demonstrate the performance of the proposed guidance law is satisfying.

scholarly journals A Fuzzy Guidance System for Rendezvous and Pursuit of Moving Targets

Robotics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 110
Author(s):  
Michael Alibani ◽  
Mario Innocenti ◽  
Lorenzo Pollini
Keyword(s):  
Direction Of Arrival ◽  
Guidance System ◽  
Target Velocity ◽  
Control Loops ◽  
Maneuvering Target ◽  
Guidance Law ◽  
Maneuvering Targets ◽  
Heading Control ◽  
Rendezvous Point ◽  
Takagi Sugeno

This article presents the development of a fuzzy guidance system (FGS) for unmanned aerial vehicles capable of pursuing and performing rendezvous with static and mobile targets. The system is designed to allow the vehicle to approach a maneuvering target from a desired direction of arrival and to terminate the rendezvous at a constant distance from the target. In order to perform a rendezvous with a maneuvering target, the desired direction of arrival is adjusted over time to always approach the target from behind, so that the aircraft and target velocity vectors become aligned. The proposed guidance system assumes the presence of an autopilot and uses a set of Takagi–Sugeno fuzzy controllers to generate the orientation and speed references for the velocity and heading control loops, given the relative position and velocity between the aircraft and the target. The FGS treats the target as a mobile waypoint in a 4-D space (position in 2-dimensions, desired crossing heading and speed) and guides the aircraft on suitable trajectories towards the target. Only when the vehicle is close enough to the rendezvous point, the guidance law is complemented with an additional linear controller to manage the terminal formation keeping phase. The capabilities of the proposed rendezvous-FGS are verified in simulation on both maneuvering and non-maneuvering targets. Finally, experimental results using a multi-rotor aerial system are presented for both fixed and accelerating targets.

scholarly journals Novel Fractional Order Calculus Extended PN for Maneuvering Targets

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Jikun Ye ◽  
Humin Lei ◽  
Jiong Li
Keyword(s):  
Fractional Order ◽  
Memory Function ◽  
Kinematic Model ◽  
Guidance System ◽  
The Novel ◽  
Fractional Order Calculus ◽  
Maneuvering Target ◽  
Guidance Law ◽  
Maneuvering Targets ◽  
Operation Rules

Based on the theory of fractional order calculus (FOC), a novel extended proportional guidance (EPN) law for intercepting the maneuvering target is proposed. In the first part, considering the memory function and filter characteristic of FOC, the novel extended PN guidance algorithm is developed based on the conventional PN after introducing the properties and operation rules of FOC. Further, with the help of FOC theory, the average load and ballistics characteristics of proposed guidance law are analyzed. Then, using the small offset kinematic model, the robustness of the new guidance law against autopilot parameters is studied theoretically by analyzing the sensitivity of the closed loop guidance system. At last, representative numerical results show that the designed guidance law obtains a better performance than the traditional PN for maneuvering target.

Low cost audio based intelligent guidance system for visually impaired people

2020 ◽  
Vol 24 (03) ◽  
pp. 515-520
Author(s):  
Vattumilli Komal Venugopal ◽  
Alampally Naveen ◽  
Rajkumar R ◽  
Govinda K ◽  
Jolly Masih
Keyword(s):  
Visually Impaired ◽  
Low Cost ◽  
Guidance System ◽  
Visually Impaired People ◽  
Impaired People

scholarly journals Autonomous Underwater Vehicles and Field of View in Underwater Operations

2021 ◽  
Vol 9 (3) ◽  
pp. 277
Author(s):  
Isaac Segovia Ramírez ◽  
Pedro José Bernalte Sánchez ◽  
Mayorkinos Papaelias ◽  
Fausto Pedro García Márquez
Keyword(s):  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Field Of View ◽  
Guidance System ◽  
Control Algorithms ◽  
Deep Waters ◽  
Underwater Cameras ◽  
Optimal Resolution ◽  
Acquisition Processes ◽  
And Control

Submarine inspections and surveys require underwater vehicles to operate in deep waters efficiently, safely and reliably. Autonomous Underwater Vehicles employing advanced navigation and control systems present several advantages. Robust control algorithms and novel improvements in positioning and navigation are needed to optimize underwater operations. This paper proposes a new general formulation of this problem together with a basic approach for the management of deep underwater operations. This approach considers the field of view and the operational requirements as a fundamental input in the development of the trajectory in the autonomous guidance system. The constraints and involved variables are also defined, providing more accurate modelling compared with traditional formulations of the positioning system. Different case studies are presented based on commercial underwater cameras/sonars, analysing the influence of the main variables in the measurement process to obtain optimal resolution results. The application of this approach in autonomous underwater operations ensures suitable data acquisition processes according to the payload installed onboard.

Augmented reality guidance system for peripheral nerve blocks

2010 ◽  
Author(s):  
Chris Wedlake ◽  
John Moore ◽  
Maxim Rachinsky ◽  
Daniel Bainbridge ◽  
Andrew D. Wiles ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Peripheral Nerve ◽  
Guidance System ◽  
Nerve Blocks ◽  
Peripheral Nerve Blocks

scholarly journals Crowd Evacuation Guidance Based on Combined Action Reinforcement Learning

Algorithms ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 26
Author(s):  
Yiran Xue ◽  
Rui Wu ◽  
Jiafeng Liu ◽  
Xianglong Tang
Keyword(s):  
Reinforcement Learning ◽  
Guidance System ◽  
Force Model ◽  
Interactive Simulation ◽  
Social Force ◽  
Novel Approach ◽  
Learning Agent ◽  
Network Output ◽  
Combined Action ◽  
Crowd Evacuation

Existing crowd evacuation guidance systems require the manual design of models and input parameters, incurring a significant workload and a potential for errors. This paper proposed an end-to-end intelligent evacuation guidance method based on deep reinforcement learning, and designed an interactive simulation environment based on the social force model. The agent could automatically learn a scene model and path planning strategy with only scene images as input, and directly output dynamic signage information. Aiming to solve the “dimension disaster” phenomenon of the deep Q network (DQN) algorithm in crowd evacuation, this paper proposed a combined action-space DQN (CA-DQN) algorithm that grouped Q network output layer nodes according to action dimensions, which significantly reduced the network complexity and improved system practicality in complex scenes. In this paper, the evacuation guidance system is defined as a reinforcement learning agent and implemented by the CA-DQN method, which provides a novel approach for the evacuation guidance problem. The experiments demonstrate that the proposed method is superior to the static guidance method, and on par with the manually designed model method.

scholarly journals A V-SLAM Guided and Portable System for Photogrammetric Applications

2021 ◽  
Vol 13 (12) ◽  
pp. 2351
Author(s):  
Alessandro Torresani ◽  
Fabio Menna ◽  
Roberto Battisti ◽  
Fabio Remondino
Keyword(s):  
Low Cost ◽  
Cost Effective ◽  
Motion Blur ◽  
Guidance System ◽  
Prototype System ◽  
Active Sensors ◽  
Localization And Mapping ◽  
Acquisition Speed ◽  
Mobile Mapping System ◽  
Slam Algorithm

Mobile and handheld mapping systems are becoming widely used nowadays as fast and cost-effective data acquisition systems for 3D reconstruction purposes. While most of the research and commercial systems are based on active sensors, solutions employing only cameras and photogrammetry are attracting more and more interest due to their significantly minor costs, size and power consumption. In this work we propose an ARM-based, low-cost and lightweight stereo vision mobile mapping system based on a Visual Simultaneous Localization And Mapping (V-SLAM) algorithm. The prototype system, named GuPho (Guided Photogrammetric System) also integrates an in-house guidance system which enables optimized image acquisitions, robust management of the cameras and feedback on positioning and acquisition speed. The presented results show the effectiveness of the developed prototype in mapping large scenarios, enabling motion blur prevention, robust camera exposure control and achieving accurate 3D results.

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