Submit to Mathematics Review for Mathematics Propose a Special Issue

Journal Menu

Journal Browser

► Journal Browser

Dynamic Modeling and Simulation for Control Systems, 2nd Edition

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Benefits of Publishing in a Special Issue
Related Special Issue
Published Papers

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Engineering Mathematics".

Deadline for manuscript submissions: closed (31 March 2024) | Viewed by 19758

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special issue Dynamic Modeling and Simulation for Control Systems, 2nd Edition book cover image

Share This Special Issue

Special Issue Editors

Prof. Dr. Adrian Olaru

E-Mail
Guest Editor

Department of Robotics and Production Systems, University Politehnica of Bucharest, 060042 Bucharest, Romania
Interests: robotics; dynamic behavior; neural networks; mobile robots; neurorehabilitation
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Gabriel Frumusanu

E-Mail
Guest Editor

Manufacturing Science and Engineering Department, “Dunarea de Jos” University of Galati, 800201 Galati, Romania
Interests: numerical modeling of machining systems; manufacturing process control; dynamics of cutting processes; chaos theory; computer-assisted design
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Catalin Alexandru

E-Mail Website
Guest Editor

Department of Product Design, Mechatronics and Environment, Transilvania University of Brasov, 500036 Brasov, Romania
Interests: mechanical systems; renewable energy systems; virtual prototyping; modeling and simulation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue titled, “Dynamic Modeling and Simulation for Control Systems II”, will address topics including the mathematical modeling of dynamic behavior; optimization algorithms; assisted theoretical and experimental research; the control of physical engineering systems; mechanical, electrical and fluid interaction components; system response analysis; feedback control systems; numerical software and software for dynamic simulation and optimization; system stability; and dynamic behavior in the frequency field. This Special Issue aims to cover important aspects about how to optimize the dynamic behavior of physical systems using special algorithms and artificial intelligence in the modeling, simulation and optimization of the components and systems from important fields such as astronautics, aerospace, avionics, robotics, manufacturing systems, mechanical engineering, power energy, materials technology and neurorehabilitation. Fuzzy and neural network control applied in complex systems will be studied. Control and simulation isotope separation processes will be developed and analyzed. This Special Issue of Mathematics will be a useful guide on techniques for the modeling, simulation and optimization of control systems in order to obtain acceptable dynamic behaviors.

Topics for this Special Issue:

Design of physical engineering systems;
Control of physical engineering systems;
Mechanical, electrical and fluid interaction between system components;
Mathematical modeling of control systems;
Fuzzy logic and control systems;
Dynamic behavior analysis;
System response analysis;
Feedback control systems;
Numerical simulation of integrated systems;
Fault detection and diagnosis;
Networked control and time-delay systems;
Frequency response;
Stability;
Control and simulation of the isotope separation process;
Software for dynamic simulation and optimization.

Prof. Dr. Adrian Olaru
Prof. Dr. Gabriel Frumusanu
Prof. Dr. Catalin Alexandru
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

mathematical modeling
numerical simulation
software simulation
data acquisition
mechanical and electrical interaction
physical engineering design
control systems
response analysis
feedback control
frequency response
stability
fuzzy logic
neural networks
artificial intelligence

Benefits of Publishing in a Special Issue

Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Related Special Issue

Dynamic Modeling and Simulation for Control Systems, 3rd Edition in Mathematics (2 articles)

Published Papers (10 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

27 pages, 8705 KiB

Open AccessArticle

Robust Control Based on Adaptative Fuzzy Control of Double-Star Permanent Synchronous Motor Supplied by PWM Inverters for Electric Propulsion of Ships

by Djamel Ziane, Samir Zeghlache, Mohamed Fouad Benkhoris and Ali Djerioui

Mathematics 2024, 12(10), 1451; https://doi.org/10.3390/math12101451 - 8 May 2024

Cited by 1 | Viewed by 785

Abstract

This study presents the development of an adaptive fuzzy control strategy for double-star PMSM-PWM inverters used in ship electrical propulsion. The approach addresses the current and speed tracking challenges of double-star permanent magnet synchronous motors (DSPMSMs) in the presence of parametric uncertainties. Initially, a modeling technique employing a matrix transformation method is introduced, generating decoupled and independent star windings to eliminate inductive couplings, while maintaining model consistency and torque control. The precise DSPMSM model serves as the foundation for an unknown nonlinear backstepping controller, approximated directly using an adaptive fuzzy controller. Through the Lyapunov direct method, system stability is demonstrated. All signals in the closed-loop system are ensured to be uniformly ultimately bounded (UUB). The proposed control system aims for low tracking errors, while also mitigating the impact of parametric uncertainties. The effectiveness of the adaptive fuzzy nonlinear control system is validated through tests conducted in hardware-in-the-loop (HIL) simulations, utilizing the OPAL-RT platform, OP4510. Full article

(This article belongs to the Special Issue Dynamic Modeling and Simulation for Control Systems, 2nd Edition)

► Show Figures

Figure 1

25 pages, 19602 KiB

Open AccessArticle

Real-Time EtherCAT-Based Control Architecture for Electro-Hydraulic Humanoid

by Maysoon Ghandour, Subhi Jleilaty, Naima Ait Oufroukh, Serban Olaru and Samer Alfayad

Mathematics 2024, 12(9), 1405; https://doi.org/10.3390/math12091405 - 3 May 2024

Cited by 2 | Viewed by 1904

Abstract

Electro-hydraulic actuators have witnessed significant development over recent years due to their remarkable abilities to perform complex and dynamic movements. Integrating such an actuator in humanoids is highly beneficial, leading to a humanoid capable of performing complex tasks requiring high force. This highlights the importance of safety, especially since high power output and safe interaction seem to be contradictory; the greater the robot’s ability to generate high dynamic movements, the more difficult it is to achieve safety, as this requires managing a large amount of motor energy before, during, and after the collision. No matter what technology or algorithm is used to achieve safety, none can be implemented without a stable control system. Hence, one of the main parameters remains the quality and reliability of the robot’s control architecture through handling a huge amount of data without system failure. This paper addresses the development of a stable control architecture that ensures, in later stages, that the safety algorithm is implemented correctly. The optimum control architecture to utilize and ensure the maximum benefit of electro-hydraulic actuators in humanoid robots is one of the important subjects in this field. For a stable and safe functioning of the humanoid, the development of the control architecture and the communication between the different components should adhere to some requirements such as stability, robustness, speed, and reduced complexity, ensuring the easy addition of numerous components. This paper presents the developed control architecture for an underdeveloped electro-hydraulic actuated humanoid. The proposed solution has the advantage of being a distributed, real-time, open-source, modular, and adaptable control architecture, enabling simple integration of numerous sensors and actuators to emulate human actions and safely interact with them. The contribution of this paper is an enhancement of the updated rate compared to other humanoids by 20% and by 40 % in the latency of the master. The results demonstrate the potential of using EtherCAT fieldbus and open-source software to develop a stable robot control architecture capable of integrating safety and security algorithms in later stages. Full article

(This article belongs to the Special Issue Dynamic Modeling and Simulation for Control Systems, 2nd Edition)

► Show Figures

Figure 1

24 pages, 10535 KiB

Open AccessArticle

Monitoring the Wear Trends in Wind Turbines by Tracking Fourier Vibration Spectra and Density Based Support Vector Machines

by Claudiu Bisu, Adrian Olaru, Serban Olaru, Adrian Alexei, Niculae Mihai and Haleema Ushaq

Mathematics 2024, 12(9), 1307; https://doi.org/10.3390/math12091307 - 25 Apr 2024

Viewed by 1867

Abstract

To make wind power more competitive, it is necessary to reduce turbine downtime and reduce costs associated with wind turbine operation and maintenance (O&M). Incorporating machine learning in the development of condition-based predictive maintenance methodologies for wind turbines can enhance their efficiency and reliability. This paper presents a monitoring method that utilizes Density Based Support Vector Machines (DBSVM) and the evolutionary Fourier spectra of vibrations. This method allows for the smart monitoring of the function evolution of the turbine. A complex optimal function (FO) for 5-degree order has been developed that will be the boundary function of the DBSVM to be timely determined from the Fourier spectrum through the magnitude–frequency and place of the failure occurring in the wind turbine drivetrains. The trend of the failure was constructed with the maximal values of the optimal frequency function for both yesthe cases of the upwind and downwind parts of the gearbox. Full article

(This article belongs to the Special Issue Dynamic Modeling and Simulation for Control Systems, 2nd Edition)

► Show Figures

Figure 1

18 pages, 439 KiB

Open AccessArticle

The Optimal Consumption, Investment and Life Insurance for Wage Earners under Inside Information and Inflation

by Rui Jiao, Wei Liu and Yijun Hu

Mathematics 2023, 11(15), 3415; https://doi.org/10.3390/math11153415 - 5 Aug 2023

Viewed by 1236

Abstract

This paper studies the dynamically optimal consumption, investment and life-insurance strategies for a wage earners under inside information and inflation. Assume that the wage earner can invest in a risk-free asset, a risky asset and an inflation-indexed bond and that the wage earner can obtain some additional information on the risky asset from the financial market. By maximizing the expected utility of the wage earner’s consumption, inheritance and terminal wealth, we obtain the dynamically optimal consumption, investment and life-insurance strategies for the wage earner. The method of this paper is mainly based on (dynamical) stochastic control theory and the technique of enlargement of filtrations. Moreover, sensitivity analysis is carried out, which reveals that a wage earner with inside information tends to increase his/her consumption and investment, while reducing his/her purchase of life insurance. Full article

(This article belongs to the Special Issue Dynamic Modeling and Simulation for Control Systems, 2nd Edition)

► Show Figures

Figure 1

28 pages, 5994 KiB

Open AccessArticle

Multi-Objective Optimization for Controlling the Dynamics of the Diabetic Population

by Karim El Moutaouakil, Abdellatif El Ouissari, Vasile Palade, Anas Charroud, Adrian Olaru, Hicham Baïzri, Saliha Chellak and Mouna Cheggour

Mathematics 2023, 11(13), 2957; https://doi.org/10.3390/math11132957 - 2 Jul 2023

Cited by 6 | Viewed by 1642

Abstract

To limit the adverse effects of diabetes, a personalized and long-term management strategy that includes appropriate medication, exercise and diet has become of paramount importance and necessity. Compartment-based mathematical control models for diabetes usually result in objective functions whose terms are conflicting, preventing the use of single-objective-based models for obtaining appropriate personalized strategies. Taking into account the conflicting aspects when controlling the diabetic population dynamics, this paper introduces a multi-objective approach consisting of four steps: (a) modeling the problem of controlling the diabetic population dynamics using a multi-objective mathematical model, (b) discretizing the model using the trapezoidal rule and the Euler–Cauchy method, (c) using swarm-intelligence-based optimizers to solve the model and (d) structuring the set of controls using soft clustering methods, known for their flexibility. In contrast to single-objective approaches, experimental results show that the multi-objective approach obtains appropriate personalized controls, where the control associated with the compartment of diabetics without complications is totally different from that associated with the compartment of diabetics with complications. Moreover, these controls enable a significant reduction in the number of diabetics with and without complications, and the multi-objective strategy saves up to 4% of the resources needed for the control of diabetes without complications and up to 18% of resources for the control of diabetes with complications. Full article

(This article belongs to the Special Issue Dynamic Modeling and Simulation for Control Systems, 2nd Edition)

► Show Figures

Figure 1

19 pages, 7643 KiB

Open AccessArticle

An Extended-State Observer Based on Smooth Super-Twisting Sliding-Mode Controller for DC-DC Buck Converters

by Dian Jiang, Yunmei Fang and Juntao Fei

Mathematics 2023, 11(13), 2835; https://doi.org/10.3390/math11132835 - 24 Jun 2023

Cited by 1 | Viewed by 1209

Abstract

This paper designs a novel smooth super-twisting extended-state observer (SSTESO)-based smooth super-twisting sliding-mode control (SSTSMC) scheme to promote the robust ability and voltage-tracking performance of DC-DC buck converters. First, an SSTESO is proposed to estimate the unknown lumped disturbance and compensate for the estimation of the voltage controller. The SSTESO is realized by constructing a novel smooth function to replace the nonlinear sign function in STESO, which can provide a faster convergence speed and higher estimation accuracy. The SSTSM controller is designed by adopting a similar smooth function to further suppress chattering and improve dynamic response. Comprehensive simulation results demonstrate that the proposed SSTESO-based SSTSMC scheme can improve the robustness and transient response of a DC-DC buck converter system in the presence of external disturbance and parameter uncertainties. Full article

(This article belongs to the Special Issue Dynamic Modeling and Simulation for Control Systems, 2nd Edition)

► Show Figures

Figure 1

20 pages, 16324 KiB

Open AccessArticle

Adaptive Super-Twisting Sliding Mode Control of Active Power Filter Using Interval Type-2-Fuzzy Neural Networks

by Jiacheng Wang, Yunmei Fang and Juntao Fei

Mathematics 2023, 11(12), 2785; https://doi.org/10.3390/math11122785 - 20 Jun 2023

Cited by 6 | Viewed by 1223

Abstract

Aiming at the unknown uncertainty of an active power filter system in practical operation, combining the advantages of self-feedback structure, interval type-2 fuzzy neural network, and super-twisting sliding mode, an adaptive super-twisting sliding mode control method of interval type-2 fuzzy neural network with self-feedback recursive structure (IT2FNN-SFR STSMC) is proposed in this paper. IT2FNN has an uncertain membership function, which can enhance the nonlinear ability and robustness of the network. The historical information will be stored and utilized by the self-feedback recursive structure (SFR) at runtime. Therefore, the novel IT2FNN-SFR is designed to improve the dynamic approximation effect of the neural network and reduce the dependence of the controller on the actual mathematical model. The adaptive rate of each weight of the neural network is designed by the Lyapunov method and gradient descent (GD) algorithm to ensure the convergence and stability of the system. Super-twisting sliding mode control (STSMC) has strong robustness, which can effectively reduce system chattering, and improve control accuracy and system performance. The gain of the integral term in the STSMC is set as a constant, and the other gain is changed adaptively whose adaptive rate is deduced through the stability proof of the neural network, which greatly reduces the difficulty of parameter adjustment. The harmonic suppression ability of the designed control strategy is verified by simulation experiments. Full article

(This article belongs to the Special Issue Dynamic Modeling and Simulation for Control Systems, 2nd Edition)

► Show Figures

Figure 1

18 pages, 2943 KiB

Open AccessArticle

State Feedback with Integral Control Circuit Design of DC-DC Buck-Boost Converter

by Humam Al-Baidhani, Abdullah Sahib and Marian K. Kazimierczuk

Mathematics 2023, 11(9), 2139; https://doi.org/10.3390/math11092139 - 3 May 2023

Cited by 8 | Viewed by 4199

Abstract

The pulse-with modulated (PWM) dc-dc buck-boost converter is a non-minimum phase system, which requires a proper control scheme to improve the transient response and provide constant output voltage during line and load variations. The pole placement technique has been proposed in the literature to control this type of power converter and achieve the desired response. However, the systematic design procedure of such control law using a low-cost electronic circuit has not been discussed. In this paper, the pole placement via state-feedback with an integral control scheme of inverting the PWM dc-dc buck-boost converter is introduced. The control law is developed based on the linearized power converter model in continuous conduction mode. A detailed design procedure is given to represent the control equation using a simple electronic circuit that is suitable for low-cost commercial applications. The mathematical model of the closed-loop power converter circuit is built and simulated using SIMULINK and Simscape Electrical in MATLAB. The closed-loop dc-dc buck-boost converter is tested under various operating conditions. It is confirmed that the proposed control scheme improves the power converter dynamics, tracks the reference signal, and maintains regulated output voltage during abrupt changes in input voltage and load current. The simulation results show that the line variation of 5 V and load variation of 2 A around the nominal operating point are rejected with a maximum percentage overshoot of 3.5% and a settling time of 5.5 ms. Full article

(This article belongs to the Special Issue Dynamic Modeling and Simulation for Control Systems, 2nd Edition)

► Show Figures

Figure 1

16 pages, 394 KiB

Open AccessArticle

A Deterministic Setting for the Numerical Computation of the Stabilizing Solutions to Stochastic Game-Theoretic Riccati Equations

by Samir Aberkane and Vasile Dragan

Mathematics 2023, 11(9), 2068; https://doi.org/10.3390/math11092068 - 27 Apr 2023

Cited by 1 | Viewed by 881

Abstract

In this paper, we are interested in the numerical aspects of the class of generalized Riccati difference equations which are involved in linear quadratic (LQ) stochastic difference games. More specifically, we address the problem of the numerical computation of the stabilizing solutions for this class of nonlinear difference equations. We propose an iterative deterministic algorithm for the computation of such a global solution. The performances of the proposed algorithm are illustrated with some numerical examples. Full article

(This article belongs to the Special Issue Dynamic Modeling and Simulation for Control Systems, 2nd Edition)

► Show Figures

Figure 1

21 pages, 662 KiB

Open AccessArticle

Gain Scheduled Fault Detection Filter for Markovian Jump Linear System with Nonhomogeneous Markov Chain

by Leonardo Carvalho, Jonathan M. Palma, Cecília F. Morais, Bayu Jayawardhana and Oswaldo L. V. Costa

Mathematics 2023, 11(7), 1713; https://doi.org/10.3390/math11071713 - 3 Apr 2023

Viewed by 1370

Abstract

In a networked control system scenario, the packet dropout is usually modeled by a time-invariant (homogeneous) Markov chain (MC) process. However, from a practical point of view, the probabilities of packet loss can vary in time and/or probability parameter dependency. Therefore, to design a fault detection filter (FDF) implemented in a semi-reliable communication network, it is important to consider the variation in time of the network parameters, by assuming the more accurate scenario provided by a nonhomogeneous jump system. Such a premise can be properly taken into account within the linear parameter varying (LPV) framework. In this sense, this paper proposes a new design method of

H_{\infty}

gain-scheduled FDF for Markov jump linear systems under the assumption of a nonhomogeneous MC. To illustrate the applicability of the theoretical solution, a numerical simulation is presented. Full article

(This article belongs to the Special Issue Dynamic Modeling and Simulation for Control Systems, 2nd Edition)

► Show Figures

Journal Menu

Journal Browser

Dynamic Modeling and Simulation for Control Systems, 2nd Edition

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Related Special Issue

Published Papers (10 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI