Test-bed for the real-time implementation of infrared target detection and tracking algorithms

1990 ◽  
Author(s):  
John F. Bronskill ◽  
Jeffrey Hodd ◽  
John S. Hepburn
Keyword(s):  
Real Time ◽  
Target Detection ◽  
Test Bed ◽  
The Real ◽  
Detection And Tracking ◽  
Tracking Algorithms

scholarly journals Implementation and intelligent gain tuning feedback–based optimal torque control of a rotary parallel robot

2021 ◽  
pp. 107754632110191
Author(s):  
Farzam Tajdari ◽  
Naeim Ebrahimi Toulkani
Keyword(s):  
Real Time ◽  
Tracking Error ◽  
Parallel Robot ◽  
Torque Control ◽  
Test Bed ◽  
Linear Quadratic ◽  
Control Effort ◽  
The Real ◽  
Unknown Disturbances ◽  
Quadratic Integral

Aiming at operating optimally minimizing error of tracking and designing control effort, this study presents a novel generalizable methodology of an optimal torque control for a 6-degree-of-freedom Stewart platform with rotary actuators. In the proposed approach, a linear quadratic integral regulator with the least sensitivity to controller parameter choices is designed, associated with an online artificial neural network gain tuning. The nonlinear system is implemented in ADAMS, and the controller is formulated in MATLAB to minimize the real-time tracking error robustly. To validate the controller performance, MATLAB and ADAMS are linked together and the performance of the controller on the simulated system is validated as real time. Practically, the Stewart robot is fabricated and the proposed controller is implemented. The method is assessed by simulation experiments, exhibiting the viability of the developed methodology and highlighting an improvement of 45% averagely, from the optimum and zero-error convergence points of view. Consequently, the experiment results allow demonstrating the robustness of the controller method, in the presence of the motor torque saturation, the uncertainties, and unknown disturbances such as intrinsic properties of the real test bed.

scholarly journals Deep Learning-Based Ground Target Detection and Tracking for Aerial Photography from UAVs

2021 ◽  
Vol 11 (18) ◽  
pp. 8434
Author(s):  
Kaipeng Wang ◽  
Zhijun Meng ◽  
Zhe Wu
Keyword(s):  
Deep Learning ◽  
Target Tracking ◽  
Target Detection ◽  
Aerial Photography ◽  
Tracking Algorithm ◽  
Aerial Image ◽  
Small Scale ◽  
Detection And Tracking ◽  
Tracking Algorithms ◽  
Ground Target

Target detection and tracking can be widely used in military and civilian scenarios. Unmanned aerial vehicles (UAVs) have high maneuverability and strong concealment, thus they are very suitable for using as a platform for ground target detection and tracking. Most of the existing target detection and tracking algorithms are aimed at conventional targets. Because of the small scale and the incomplete details of the targets in the aerial image, it is difficult to apply the conventional algorithms to aerial photography from UAVs. This paper proposes a ground target image detection and tracking algorithm applied to UAVs using a revised deep learning technology. Aiming at the characteristics of ground targets in aerial images, target detection algorithms and target tracking algorithms are improved. The target detection algorithm is improved to detect small targets on the ground. The target tracking algorithm is designed to recover the target after the target is lost. The target detection and tracking algorithm is verified on the aerial dataset.

HIL Operation of Single Cylinder Research Engines to Optimize the Transient Behavior of Large Gas Engines

2017 ◽  
Author(s):  
Jan Zelenka ◽  
Philipp Mayr ◽  
Gerhard Pirker ◽  
Andreas Wimmer
Keyword(s):  
Rapid Prototyping ◽  
Real Time ◽  
Control Strategies ◽  
Measurement Data ◽  
Transient Behavior ◽  
Special Focus ◽  
Test Bed ◽  
Single Cylinder ◽  
The Real ◽  
Stage Of Development

To enable sustainable power generation through increasing shares of renewable energy, it is necessary to find flexible solutions that use conventional fossil fuels to compensate for volatile energy production from the wind and sun in order to stabilize the electrical grid. Modern large bore engines fueled by gas are already able to ramp up or shut down production quickly and also provide high efficiency throughout all load conditions. Nevertheless, transient capabilities of these engines must be improved even more in order to compete with diesel engines in applications with the highest transient requirements. To meet these demands, sophisticated actuators and control strategies are required. Testing of these components and strategies should already be conducted in an early development phase using rapid prototyping simulation and measurements on single cylinder engines instead of expensive multicylinder engine tests. The first section of this paper shows how engine controller functions for transient operation based on rapid prototyping models and real-time capable models can be derived and tested. This enables the capabilities of different control strategies to be quantified in order to improve transient performance in an early stage of development. The second section of the paper presents a methodology for transferring the transient behavior of a large multicylinder engine to a single cylinder test bed using a hardware-in-the-loop (HiL) approach with real time capable simulation models. A description of the demands on hardware and software is provided followed by a description of the overall system, after which the application of the real-time capable models on the real-time controllers of the test bed system is introduced. Finally, the models with measurement data from the single cylinder engine are compared with the multicylinder engine with a special focus on block loads and ramping the engine at constant speed.

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