The Regulation of an Electric Oven and an Inverted Pendulum

Balcazar, Ricardo; Rubio, José de Jesús; Orozco, E. A.; Cordova, Daniel Andres; Ochoa, Genaro; García, Enrique; Pacheco, Jaime; Gutiérrez, Guadalupe Juliana; Mújica-Vargas, Dante; Aguilar-Ibáñez, Carlos

doi:10.3390/sym14040759

Cited by 32 publications

(9 citation statements)

References 22 publications

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“…This process can be divided into three stages: detection, data association, and trajectory generation. Although some trackers [23,26,32,43,44,48] have achieved preferable performances, the missing detection of small objects, insufficient motion information [2], and track drifting [21,29] caused by occlusion, ambiguity, or vibration are still significant challenges. To address these issues, some advanced methodologies are proposed, such as heatmap, Kalman filter, and trajectory reconnection.…”

Section: Introductionmentioning

confidence: 99%

NCT:noise-control multi-object tracking

Zeng

You

Shen

et al. 2023

Complex Intell. Syst.

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Multi-Object Tracking (MOT) is an important topic in computer vision. Recent MOT methods based on the anchor-free paradigm trade complicated hierarchical structures for tracking performance. However, existing anchor-free MOT methods ignore the noise in detection, data association, and trajectory reconnection stages, which results in serious problems, such as missing detection of small objects, insufficient motion information, and trajectory drifting. To solve these problems, this paper proposes Noise-Control Tracker (NCT), which focuses on the noise-control design of detection, association, and reconnection. First, a prior depth denoise method is introduced to suppress the fusion feature redundant noise, which can recover the gradient information of the heatmap fusion features. Then, the Smoothing Gain Kalman filter is designed, which combines the Gaussian function with the adaptive observation coefficient matrix to stabilize the mutation noise of Kalman gain. Finally, to address the drift noise issue, the gradient boosting reconnection context mechanism is designed, which realizes adaptive trajectory reconnection to effectively fill the gaps in trajectories. With the assistance of the plug-and-play noise-control method, the experimental results on MOTChallenge 16 &17 datasets indicate that the NCT can achieve better performance than other state-of-the-art trackers.

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Section: Introductionmentioning

confidence: 99%

NCT:noise-control multi-object tracking

Zeng

You

Shen

et al. 2023

Complex Intell. Syst.

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“…Orozco et al corrected the linearization technique [ 7 ]. Balcazar et al compared the proportional integral differential regulator, the first-order sliding mode regulator, and the second-order sliding mode regulator to adjust two different types of mathematical models [ 8 ]. In order to find the optimal travel cost of all crane operations in a given time period, Marzouk and Abubakr proposed tower crane type selection decision support based on building information modeling and genetic algorithm [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Intelligent Optimization of Tower Crane Location and Layout Based on Firefly Algorithm

Liu

Zhang

Han

et al. 2022

Computational Intelligence and Neuroscience

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The existing tower crane positioning layout mainly depends on the experience of construction personnel, and the best tower crane positioning can be found through a large number of manual data calculation. This manual method is time-consuming and impractical. In view of this, aiming at the current situation that building information modeling (BIM) software can only obtain the relative coordinates of components, this article puts forward the key technology of importing computer-aided design (CAD) graphics into geographic information system (GIS) software to automatically obtain the world coordinate information. By clarifying the transfer relationship between the component material supply point, the component initial positioning point, and the tower crane optional positioning point, as well as the cooperative relationship between each positioning point and the tower crane operation, the tower crane positioning optimization model is formed, and the firefly algorithm is used to automatically calculate and generate the best positioning layout method of the tower crane on the project site. In this study, the vertical transportation and positioning of components are studied, and intelligent construction is formed by integrating information technology. It can further enrich the functions of perception, analysis, decision-making, and optimization; realize the decision-making intelligence of industrial buildings; and achieve the organic unity of engineering construction execution system and decision-making command system.

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“…Moreover, the SNSNS are widely used and reported in many physical systems. [8][9][10][11][12][13][14][15][16][17][18] It is significant and challenging to design the controller for such system.…”

Section: Introductionmentioning

confidence: 99%

“…For SNSNS, all the system functions contain the whole state variables, and there is no affine appearance of the variables to be utilized as controller design. Moreover, the SNSNS are widely used and reported in many physical systems 8‐18 . It is significant and challenging to design the controller for such system.…”

Section: Introductionmentioning

confidence: 99%

Event‐triggered adaptive neural control for stochastic nontriangular structure nonlinear systems with multisensor and actuator failures: The practical fixed‐time stability

Ren

Liu

2022

Adaptive Control & Signal

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Summary This article is concerned with the issue of event‐triggered adaptive fixed‐time control with sensor and actuator faults for stochastic nontriangular structure nonlinear system (SNSNS). The main difficulty in this article is the design of a novel and stable controller for SNSNS to compensate for the effect of sensor and actuator faults with event‐triggered control (ETC) in a unified framework. The mean value theorem (MVT) and ETC method are introduced to solve the questions of nonaffine structure and communication burden. Meanwhile, with the aid of adaptive neural network and fixed‐time theory, a novel controller is proposed by backstepping technology, which can ensure all the closed‐loop signals are bounded in probability within a fixed time as well avoid Zeno behavior. At last, the simulation is carried out to demonstrate the effectiveness of the proposed scheme.

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The Regulation of an Electric Oven and an Inverted Pendulum

Cited by 32 publications

References 22 publications

NCT:noise-control multi-object tracking

NCT:noise-control multi-object tracking

Intelligent Optimization of Tower Crane Location and Layout Based on Firefly Algorithm

Event‐triggered adaptive neural control for stochastic nontriangular structure nonlinear systems with multisensor and actuator failures: The practical fixed‐time stability

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