Research

13 pages, 3530 KiB

Open AccessArticle

Modeling of 2R Planar Dumbbell Stacker Robot Locomotion Using Force Control for Gripper Dexterous Manipulation

by Sergei Kondratev and Victor Meshcheryakov

Computation 2022, 10(9), 143; https://doi.org/10.3390/computation10090143 - 23 Aug 2022

Cited by 3 | Viewed by 2083

This paper describes a novel approach to the robotic system’s dexterous manipulator arm design. A simulation model of the robotic system is developed in the MATLAB/Simulink environment. The designed gripper moves the dumbbells from one shelf to another using impedance and dynamics control. [...] Read more.

This paper describes a novel approach to the robotic system’s dexterous manipulator arm design. A simulation model of the robotic system is developed in the MATLAB/Simulink environment. The designed gripper moves the dumbbells from one shelf to another using impedance and dynamics control. The novel approach to contact force control was tested. For the most accurate simulation, the size and mass parameters of the manipulator and dumbbells are determined. In addition, various force parameters such as normal, friction and damping were evaluated. The dynamic behavior of the robotic system was described by the Lagrange dynamics equations to find the acceleration of the robot’s joints during friction interaction, and the energy performance was described. The corresponding dynamic model and its analysis are the starting point for its successful solution. The analytical and numerical descriptions are obtained and can be further used for computer simulation of the system, calculation of dynamic constraints, optimization of manipulator design, synthesis of trajectory planner and motion control algorithms of dexterous manipulative robotic systems. Full article

(This article belongs to the Special Issue Control Systems, Mathematical Modeling and Automation)

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16 pages, 1266 KiB

Open AccessArticle

Cognitive Hybrid Intelligent Diagnostic System: Typical Architecture

by Sophiya Rumovskaya

Computation 2022, 10(5), 66; https://doi.org/10.3390/computation10050066 - 22 Apr 2022

Cited by 2 | Viewed by 1912

Abstract

The research refers to the modeling of the meaningful and relatively stable visual-figurative and verbal-sign representation of real problems in medical diagnostics of the human organs and systems. The core results of the research are presented. Here, a new visual metalanguage is proposed. [...] Read more.

The research refers to the modeling of the meaningful and relatively stable visual-figurative and verbal-sign representation of real problems in medical diagnostics of the human organs and systems. The core results of the research are presented. Here, a new visual metalanguage is proposed. It describes the solution of a diagnostic problem by combining several interconnected processes of reasoning in different languages defining “a state of human organs and systems”, “a diagnostic problem” and elements of its decomposition. In the paper, a subject-figurative model of the cognitive hybrid intelligent diagnostic system, its typical architecture, and a synthesis algorithm are provided. Due to the integration of imitation of an internal subject-figurative vision of medical diagnostic problems and the corresponding communication statements of private diagnoses with imitation of the behavior inherent for councils in problem situations, the future implementation of such system prototypes will reduce the number of medical errors. The further stage of this research is the approbation of all solutions for the problem of diagnosing diseases of the pancreas on the materials of the Kaliningrad Regional Clinical Hospital and experimental study of the system. The research is limited by the subject area of medicine but can be generalized to the other areas. Full article

(This article belongs to the Special Issue Control Systems, Mathematical Modeling and Automation)

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17 pages, 663 KiB

Open AccessArticle

Aggregating Composite Indicators through the Geometric Mean: A Penalization Approach

by Francesca Mariani and Mariateresa Ciommi

Computation 2022, 10(4), 64; https://doi.org/10.3390/computation10040064 - 18 Apr 2022

Cited by 5 | Viewed by 2856

Abstract

In this paper, we introduce a penalized version of the geometric mean. In analogy with the Mazziotta Pareto Index, this composite indicator is derived as a product between the geometric mean and a penalization term to account for the unbalance among indicators. The [...] Read more.

In this paper, we introduce a penalized version of the geometric mean. In analogy with the Mazziotta Pareto Index, this composite indicator is derived as a product between the geometric mean and a penalization term to account for the unbalance among indicators. The unbalance is measured in terms of the (horizontal) variability of the normalized indicators opportunely scaled and transformed via the Box–Cox function of order zero. The penalized geometric mean is used to compute the penalized Human Development Index (HDI), and a comparison with the geometric mean approach is presented. Data come from the Human Development Data Center for 2019 and refer to the classical three dimensions of HDI. The results show that the new method does not upset the original ranking produced by the HDI but it impacts more on countries with poor performances. The paper has the merit of proposing a new reading of the Mazziotta Pareto Index in terms of the reliability of the arithmetic mean as well as of generalizing this reading to the geometric mean approach. Full article

(This article belongs to the Special Issue Control Systems, Mathematical Modeling and Automation)

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31 pages, 20055 KiB

Open AccessArticle

Modeling the Territorial Structure Dynamics of the Northern Part of the Volga-Akhtuba Floodplain

by Inessa I. Isaeva, Alexander A. Voronin, Alexander V. Khoperskov and Mikhail A. Kharitonov

Computation 2022, 10(4), 62; https://doi.org/10.3390/computation10040062 - 11 Apr 2022

Cited by 8 | Viewed by 2384

Abstract

The subject of our study is the tendency to reduce the floodplain area of regulated rivers and its impact on the degradation of the socio-environmental systems in the floodplain. The aim of the work is to create a new approach to the analysis [...] Read more.

The subject of our study is the tendency to reduce the floodplain area of regulated rivers and its impact on the degradation of the socio-environmental systems in the floodplain. The aim of the work is to create a new approach to the analysis and forecasting of the multidimensional degradation processes of floodplain territories under the influence of natural and technogenic factors. This approach uses methods of hydrodynamic and geoinformation modeling, statistical analysis of observational data and results of high-performance computational experiments. The basis of our approach is the dynamics model of the complex structure of the floodplain. This structure combines the characteristics of the frequency ranges of flooding and the socio-environmental features of various sites (cadastral data of land use). Modeling of the hydrological regime is based on numerical shallow water models. The regression model of the technogenic dynamics of the riverbed allowed us to calculate corrections to the parameters of real floods that imitate the effect of this factor. This made it possible to use digital maps of the modern topography for hydrodynamic modeling and the construction of floods maps for past and future decades. The technological basis of our study is a set of algorithms and software, consisting of three modules. The data module includes, first of all, the cadastres of the territory of the Volga-Akhtuba floodplain (VAF, this floodplain is the interfluve of the Volga and Akhtuba rivers for the last 400 km before flowing into the Caspian Sea), satellite and natural observation data, spatial distributions of parameters of geoinformation and hydrodynamic models. The second module provides the construction of a multilayer digital model of the floodplain area, digital maps of floods and their aggregated characteristics. The third module calculates a complex territorial structure, criteria for the state of the environmental and socio-economic system (ESES) and a forecast of its changes. We have shown that the degradation of the ESES of the northern part of the VAF is caused by the negative dynamics of the hydrological structure of its territory, due to the technogenic influence the hydroelectric power station on the Volga riverbed. This dynamic manifests itself in a decrease in the stable flooded area and an increase in the unflooded and unstable flooded areas. An important result is the forecast of the complex territorial structure and criteria for the state of the interfluve until 2050. Full article

(This article belongs to the Special Issue Control Systems, Mathematical Modeling and Automation)

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12 pages, 570 KiB

Open AccessArticle

Applying Machine Learning Methods and Models to Explore the Structure of Traffic Accident Data

by Anton Sysoev, Vladimir Klyavin, Alexandra Dvurechenskaya, Albert Mamedov and Vladislav Shushunov

Computation 2022, 10(4), 57; https://doi.org/10.3390/computation10040057 - 31 Mar 2022

Viewed by 2253

Abstract

The problem of reducing the increasing number of road traffic accidents has become more relevant in recent years. According to the United Nations plan this number has to be halved by 2030. A very effective way to handle it is to apply the [...] Read more.

The problem of reducing the increasing number of road traffic accidents has become more relevant in recent years. According to the United Nations plan this number has to be halved by 2030. A very effective way to handle it is to apply the machine learning paradigm to retrospective road traffic accident datasets. This case study applies machine learning techniques to form typical “portraits” of drivers violating road traffic rules by clustering available data into seven homogeneous groups. The obtained results can be used in forming effective marketing campaigns for different target groups. Another relevant problem under consideration is to use available retrospective statistics on mechanical road traffic accidents without victims to estimate the probable type of road traffic accident for the driver taking into account her/his personal features (such as social characteristics, typical road traffic rule violations, driving experience, and age group). For this purpose several machine learning models were applied and the results were discussed. Full article

(This article belongs to the Special Issue Control Systems, Mathematical Modeling and Automation)

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19 pages, 848 KiB

Open AccessArticle

Short-Term Mortality Fluctuations and Longevity Risk-Adjusted Age: Learning the Resilience of a Country to a Health Shock

by Gloria Polinesi, Maria Cristina Recchioni, Andrea Rimondi and Anton Sysoev

Computation 2022, 10(4), 47; https://doi.org/10.3390/computation10040047 - 22 Mar 2022

Viewed by 1974

Abstract

Recent studies have attempted to measure differences in lifestyle quality across the world. This paper contributes to this strand of literature by extending the indicator introduced in Milevsky (2020), i.e., “longevity-risk-adjusted global age” (LRaG age), to deal with the new short-term mortality fluctuation [...] Read more.

Recent studies have attempted to measure differences in lifestyle quality across the world. This paper contributes to this strand of literature by extending the indicator introduced in Milevsky (2020), i.e., “longevity-risk-adjusted global age” (LRaG age), to deal with the new short-term mortality fluctuation data series freely available from the Human Mortality Database. The new weekly data on mortality allow measuring weekly biological age. The weekly differences between biological and chronological ages across countries were used to assess country resilience to the COVID-19 pandemic in terms of excess mortality and health expenditure. Countries with a biological age lower than the chronological age had a lower excess mortality in 2020–2021 and a lower health expenditure, thus indicating some resilience to the shock of COVID-19. Full article

(This article belongs to the Special Issue Control Systems, Mathematical Modeling and Automation)

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15 pages, 2047 KiB

Open AccessArticle

DC Drive Adaptive Speed Controller Based on Hyperstability Theory

by Anton Glushchenko, Konstantin Lastochkin and Vladislav Petrov

Computation 2022, 10(3), 40; https://doi.org/10.3390/computation10030040 - 14 Mar 2022

Cited by 3 | Viewed by 1742

Abstract

The scope of this research is to develop a hyperstable adaptive control system of a direct current (DC) drive speed for effective load torque attenuation. The proposed speed controller is based on the model reference adaptive control framework and integrated into the conventional [...] Read more.

The scope of this research is to develop a hyperstable adaptive control system of a direct current (DC) drive speed for effective load torque attenuation. The proposed speed controller is based on the model reference adaptive control framework and integrated into the conventional DC drive cascade control system. Its main features are as follows: (1) the boundedness of the control action signal, as well as the armature current control loop non-stationarities, are taken into consideration with the help of the reference model hedging technique; (2) its inputs include only measurable signals, thus there is no need to use any kind of state estimators; (3) it attenuates the disturbances, which are matched with its control action signal, particularly, the inertia moment non-stationarity and load torque. The asymptotic hyperstability of the obtained DC drive control system is proven with the help of Lyapunov’s theorems and Popov’s criterion. The numerical experiments corroborate the obtained results. They include the demonstration of disadvantages of the conventional cascade control system under conditions of the drive parameters’ non-stationarity and advantages of the proposed solution for different disturbance types and amplitudes. Full article

(This article belongs to the Special Issue Control Systems, Mathematical Modeling and Automation)

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14 pages, 468 KiB

Open AccessArticle

TS Fuzzy Robust Sampled-Data Control for Nonlinear Systems with Bounded Disturbances

by Thangavel Poongodi, Prem Prakash Mishra, Chee Peng Lim, Thangavel Saravanakumar, Nattakan Boonsatit, Porpattama Hammachukiattikul and Grienggrai Rajchakit

Computation 2021, 9(12), 132; https://doi.org/10.3390/computation9120132 - 08 Dec 2021

Cited by 3 | Viewed by 2342

Abstract

We investigate robust fault-tolerant control pertaining to Takagi–Sugeno (TS) fuzzy nonlinear systems with bounded disturbances, actuator failures, and time delays. A new fault model based on a sampled-data scheme that is able to satisfy certain criteria in relation to actuator fault matrix is [...] Read more.

We investigate robust fault-tolerant control pertaining to Takagi–Sugeno (TS) fuzzy nonlinear systems with bounded disturbances, actuator failures, and time delays. A new fault model based on a sampled-data scheme that is able to satisfy certain criteria in relation to actuator fault matrix is introduced. Specifically, we formulate a reliable controller with state feedback, such that the resulting closed-loop-fuzzy system is robust, asymptotically stable, and able to satisfy a prescribed

H_{\infty}

performance constraint. Linear matrix inequality (LMI) together with a proper construction of the Lyapunov–Krasovskii functional is leveraged to derive delay-dependent sufficient conditions with respect to the existence of robust

H_{\infty}

controller. It is straightforward to obtain the solution by using the MATLAB LMI toolbox. We demonstrate the effectiveness of the control law and less conservativeness of the results through two numerical simulations. Full article

(This article belongs to the Special Issue Control Systems, Mathematical Modeling and Automation)

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22 pages, 8349 KiB

Open AccessArticle

Nonlinear Dynamics and Performance Analysis of a Buck Converter with Hysteresis Control

by Carlos I. Hoyos Velasco, Fredy Edimer Hoyos Velasco and John E. Candelo-Becerra

Computation 2021, 9(10), 112; https://doi.org/10.3390/computation9100112 - 19 Oct 2021

Cited by 3 | Viewed by 2579

Abstract

This paper presents the mathematical modeling and experimental implementation of a Buck converter with hysteresis control. The system is described using a state-space model. Theoretical and simulation studies show that the zero hysteresis control leads to an equilibrium point with the implication of [...] Read more.

This paper presents the mathematical modeling and experimental implementation of a Buck converter with hysteresis control. The system is described using a state-space model. Theoretical and simulation studies show that the zero hysteresis control leads to an equilibrium point with the implication of an infinite commutation frequency, while the use of a constant hysteresis band induces a limit cycle with a finite switching frequency. There exists a tradeoff between voltage output ripple and transistor switching frequency. An experimental prototype for the Buck power converter is built, and theoretical results are verified experimentally. In general terms, the Buck converter with the hysteresis control shows a robust control with respect to load variations, with undesired high switching frequency taking place for a very narrow hysteresis band, which is solved by tuning the hysteresis band properly. Full article

(This article belongs to the Special Issue Control Systems, Mathematical Modeling and Automation)

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15 pages, 6013 KiB

Open AccessArticle

Performance of the Boost Converter Controlled with ZAD to Regulate DC Signals

by Simeón Casanova Trujillo, John E. Candelo-Becerra and Fredy E. Hoyos

Computation 2021, 9(9), 96; https://doi.org/10.3390/computation9090096 - 04 Sep 2021

Cited by 1 | Viewed by 1655

Abstract

This paper presents the performance of a boost converter controlled with a zero average dynamics technique to regulate direct current signals. The boost converter is modeled in a compact form, and a variable change is performed to depend only on the

γ

parameter. [...] Read more.

This paper presents the performance of a boost converter controlled with a zero average dynamics technique to regulate direct current signals. The boost converter is modeled in a compact form, and a variable change is performed to depend only on the

γ

parameter. A new sliding surface is proposed, where it is possible to regulate both the voltage and the current with low relative errors with respect to the reference signals. It is analytically demonstrated that the approximation of the switching surface by a piecewise linear technique is efficient in controlling the system. It is shown numerically that for certain operating conditions, the system is evolved into a chaotic attractor. The zero average dynamics technique implemented in the boost converter has good regulation, due to the presence of zones in the bi-parametric space. Furthermore, the zero average dynamics technique regulates the voltage well and presents a chaotic attractor with low steady-state error. Full article

(This article belongs to the Special Issue Control Systems, Mathematical Modeling and Automation)

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