Advanced Nonlinear and Learning-Based Control Techniques for Complex Dynamical Systems, 2nd Edition

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: 15 July 2025 | Viewed by 3779

Special Issue Editors


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Guest Editor
Robotics Engineering Department, Columbus State University, Columbus, GA 31907, USA
Interests: thermoacustics; synthetic jet actuators; flow-induced-noise control; marine vehicle control; flow control
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E-Mail Website
Guest Editor
Robotics Engineering Program, Columbus State University, Columbus, GA 31907, USA
Interests: real-time learning-based control; machine learning; multi-agent systems; control & systems theory; robotics
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Aerospace and Mechanical Engineering, University of Oklahoma, Norman, OK 73019, USA
Interests: real-time optimization-based control and estimation methods, nonlinear control, and machine learning, with special emphasis on foundational theory and experimental realization on robotic and autonomous systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

There has been a great deal of excitement during the recent past over the emergence of new mathematical techniques for the modeling and analysis of complex dynamical systems. For example, recent years have witnessed an explosion of work on the development of both learning-based and nonlinear control system models in a geometric form that are globally defined without singularities or ambiguities. These models are applied to the motion planning and feedback control of constrained robotic systems. These fascinating topics require the use of diverse parts of mathematics. Nonlinear and learning-based control system theory and various design techniques are used widely in the robotics arena, especially in developing nonlinear robust control algorithms. The design of these systems involves advanced techniques including nonlinear optimization, machine learning, adaptive estimation, and nonlinear observer and control design methodologies. In this context, this Special Issue welcomes the submission of papers from a wide range of researchers in applied mathematics and various engineering disciplines.

Potential topics include, but are not limited to:

  • Nonlinear optimization techniques;
  • Nonlinear observer design;
  • Nonlinear adaptive estimation;
  • Nonlinear robust control;
  • Reduced-order modeling and control;
  • Learning-based/intelligent control;
  • Neuro-adaptive control;
  • Gaussian-process-based control methods;
  • Real-time learning-based control;
  • Multi-agent systems control;
  • Formation/flocking control;
  • Geometric control theory and applications.

Prof. Dr. Mahmut Reyhanoglu
Dr. Mohammad Jafari
Dr. Erkan Kayacan
Guest Editors

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Keywords

  • optimization
  • observer design
  • adaptive control
  • learning control
  • intelligent control
  • robust control
  • formation control
  • geometric control

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Related Special Issue

Published Papers (4 papers)

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Research

16 pages, 2300 KiB  
Article
Learning-Enabled Robust Control of Thermoacoustic Oscillations
by Mahmut Reyhanoglu and Mohammad Jafari
Electronics 2025, 14(9), 1771; https://doi.org/10.3390/electronics14091771 - 27 Apr 2025
Viewed by 136
Abstract
This work addresses the learning-enabled robust control of thermoacoustic systems under uncertainties and unknown disturbances. A widely recognized thermoacoustic system model is considered, incorporating monopole-like actuators and sensor arrays for demonstration. The model is reformulated into a set of ordinary differential equations (ODEs) [...] Read more.
This work addresses the learning-enabled robust control of thermoacoustic systems under uncertainties and unknown disturbances. A widely recognized thermoacoustic system model is considered, incorporating monopole-like actuators and sensor arrays for demonstration. The model is reformulated into a set of ordinary differential equations (ODEs) suitable for control design. The learning-enabled control law is derived by minimizing a cost function that reflects the target closed-loop error dynamics using a gradient descent method. The closed-loop system stability is established through a pseudolinear system approach. The learning-enabled control law effectively mitigates the unwanted effects of uncertainties and disturbances. The controller performance is validated using a combustion system model featuring two modes and two actuators. Full article
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20 pages, 27886 KiB  
Article
Mechanical Design and Analysis of a Novel Symmetrical 2T1R Parallel Robot
by Qi Zou, Yiwei Zhang, Yuancheng Shi, Shuo Zhang and Yueyuan Zhang
Electronics 2025, 14(8), 1596; https://doi.org/10.3390/electronics14081596 - 15 Apr 2025
Viewed by 185
Abstract
The planar parallel robots are widely employed in industrial applications due to simple geometry, few linkage interferences, and a large, reachable workspace. The symmetric geometry can bring significant convenience to parallel robots. The complexity of the mathematic models can be simplified since only [...] Read more.
The planar parallel robots are widely employed in industrial applications due to simple geometry, few linkage interferences, and a large, reachable workspace. The symmetric geometry can bring significant convenience to parallel robots. The complexity of the mathematic models can be simplified since only one calculation method can be proposed to deal with various kinematic limbs in a parallel manipulator. The symmetric geometry can ease the assembly and maintenance procedures due to the modular design of linkages/joints. A novel 2-translation and 1-rotation (2T1R) parallel robot with symmetric geometry is proposed in this research. There is one closed loop in each kinematic limb, and 18 revolute joints are applied in its planar structure. Both the inverse and direct kinematic models are explored. The first-order relationship between robot inputs and outputs are constructed. Various singularity configurations are obtained based on the Jacobian matrix. The reachable workspace is resolved by the discrete spatial searching methodology, followed by the impacts originating from various linkages. The dexterity analysis of the parallel robot is conducted. Full article
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23 pages, 7332 KiB  
Article
Determination of Anchor Drop Sequence during Vessel Anchoring Operations Based on Expert Knowledge Base and Hydrometeorological Conditions
by Jakub Wnorowski and Andrzej Łebkowski
Electronics 2024, 13(1), 176; https://doi.org/10.3390/electronics13010176 - 30 Dec 2023
Cited by 1 | Viewed by 1589
Abstract
Presently, the most common technique for maintaining a ship’s location is dynamic positioning, which uses a series of thrusters to hold its position. This method is resilient to moderate hydro-meteorological conditions, eliminating the need for extensive preliminary steps before initiating positioning operations. An [...] Read more.
Presently, the most common technique for maintaining a ship’s location is dynamic positioning, which uses a series of thrusters to hold its position. This method is resilient to moderate hydro-meteorological conditions, eliminating the need for extensive preliminary steps before initiating positioning operations. An alternative approach involves station keeping using a set of anchors, where thrusters are not employed, necessitating careful planning of the anchorage in light of hydro-meteorological conditions. Presently, in vessels using this anchoring method, the captain determines the order of anchor drops, taking into account the prevailing weather conditions, the ship’s maneuvering abilities, and vessel capability plots. This article introduces a novel algorithm that uses sensor-acquired weather data and a cognitive knowledge base to establish the best sequence for anchor drops. This innovation represents a significant stride towards the automation of the anchoring process. By using the anchorage planning algorithm presented in this publication, it has been possible to reduce the time required for anchor deployment by about 52%, due to the preparation of the anchor deployment strategy in port. A reduction in energy consumption of about 8% was also achieved. Full article
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22 pages, 5673 KiB  
Article
A Sliding Mode Controller with Signal Transmission Delay Compensation for the Parallel DC/DC Converter’s Network Control System
by Juan Yu, Weiqi Zhang, Wenwen Xiong and Yanmin Wang
Electronics 2024, 13(1), 121; https://doi.org/10.3390/electronics13010121 - 28 Dec 2023
Cited by 2 | Viewed by 1180
Abstract
The network control system (NCS) of the parallel DC/DC converter is always affected by the signal transmission delay, and the ideal output performance is lost. In this paper, a typical parallel buck converter is taken as the research object. Firstly, a sliding mode [...] Read more.
The network control system (NCS) of the parallel DC/DC converter is always affected by the signal transmission delay, and the ideal output performance is lost. In this paper, a typical parallel buck converter is taken as the research object. Firstly, a sliding mode controller (SMC) in the discrete domain is designed to enhance the robustness of the system. On this basis, the effects of different delays on the stability of the converter’s NCS are analyzed, and the actual effects of long/short delays on the converter’s NCS are obtained. To further solve the problem of damage to transmitted signals of the NCS by long delay, the SM controller designed in this paper is improved by incorporating a multi-step prediction method. This enhancement enables effective prediction and compensation of the delay signals lost by the NCS, ensuring the output performance of the parallel buck converter. Finally, the superiority of the proposed method is verified by designing simulations and experiments. Full article
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