Robust Human Tracking of a Crawler Robot

Carrying out firefighting activities at disaster sites is extremely difficult. Therefore, robots that support and enhance these operations are required. In this paper, a crawler robot that tracks the moving path of a firefighter is proposed. It is commonly believed that trained firefighters select the best route; thus, it was assumed that this route is the easiest for the crawler robot as well. Using two 3D light detection and ranging sensors, once the firefighter’s coordinates are detected, the coordinates are combined with 3D simultaneous localization and mapping results, then a target path is generated. The crawler robot follows the path using inverse optimal tracking control. The controller has a stability margin that guarantees robustness, which is an ideal property for disaster response robots used in severe conditions. The results of several experiments show that the proposed system is effective and practical for the crawler robot.

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Human tracking control system using Kinect sensors on wheelchair based on Arduino

Journal of Physics Conference Series ◽

10.1088/1742-6596/1436/1/012003 ◽

2020 ◽

Vol 1436 ◽

pp. 012003

Author(s):

H Hamadi ◽

B Suhendro ◽

M S Alamsyah ◽

M Ibrahim

Keyword(s):

Control System ◽

Tracking Control ◽

Human Tracking

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Robust Optimal Tracking Control of a Full-Bridge DC-AC Converter

Applied Sciences ◽

10.3390/app11031211 ◽

2021 ◽

Vol 11 (3) ◽

pp. 1211

Author(s):

En-Chih Chang ◽

Chun-An Cheng ◽

Rong-Ching Wu

Keyword(s):

Steady State ◽

Digital Signal Processor ◽

Tracking Control ◽

Harmonic Distortion ◽

Digital Signal ◽

Fast Convergence ◽

Solution Quality ◽

Hybrid Strategy ◽

Optimal Tracking ◽

Optimal Tracking Control

This paper develops a full-bridge DC-AC converter, which uses a robust optimal tracking control strategy to procure a high-quality sine output waveshape even in the presence of unpredictable intermissions. The proposed strategy brings out the advantages of non-singular fast convergent terminal attractor (NFCTA) and chaos particle swarm optimization (CPSO). Compared with a typical TA, the NFCTA affords fast convergence within a limited time to the steady-state situation, and keeps away from the possibility of singularity through its sliding surface design. It is worth noting that once the NFCTA-controlled DC-AC converter encounters drastic changes in internal parameters or the influence of external non-linear loads, the trembling with low-control precision will occur and the aggravation of transient and steady-state performance yields. Although the traditional PSO algorithm has the characteristics of simple implementation and fast convergence, the search process lacks diversity and converges prematurely. So, it is impossible to deviate from the local extreme value, resulting in poor solution quality or search stagnation. Thereby, an improved version of traditional PSO called CPSO is used to discover global optimal NFCTA parameters, which can preclude precocious convergence to local solutions, mitigating the tremor as well as enhancing DC-AC converter performance. By using the proposed stable closed-loop full-bridge DC-AC converter with a hybrid strategy integrating NFCTA and CPSO, low total harmonic distortion (THD) output-voltage and fast dynamic load response are generated under nonlinear rectifier-type load situations and during sudden load changes, respectively. Simulation results are done by the Matlab/Simulink environment, and experimental results of a digital signal processor (DSP) controlled full-bridge DC-AC converter prototype confirm the usefulness of the proposed strategy.

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