Nonlinear Analysis and Control of Electronic Systems

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

Deadline for manuscript submissions: 15 July 2026 | Viewed by 1706

Editors


E-Mail Website
Guest Editor
School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
Interests: control and analysis of nonlinear systems

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Guest Editor
Robotics College | Artificial Intelligence College, Beijing Union University, Beijing 100101, China
Interests: modeling and control of complex systems

Special Issue Information

Dear Colleagues,

Electronic systems are inherently nonlinear, arising from the physical characteristics of components (e.g., diodes, transistors, and power converters) and operational constraints (e.g., saturation, hysteresis, and dead zones). Nonlinear electronic systems often exhibit complex behaviors—such as bifurcations, chaos, limit cycles, and jump phenomena—that cannot be adequately described by linearization alone. These nonlinearities may lead to performance degradation (e.g., distortion in amplifiers) or even system instability (e.g., oscillations in power electronics); however, they can also be harnessed to enable innovative functionalities (e.g., frequency mixing in communication systems).

For electronic systems, understanding and controlling these nonlinear behaviors is critical to optimizing performance, ensuring reliability, and advancing cutting-edge electronic technologies. Methods of nonlinear analysis provide the foundation for decoding the dynamics of electronic systems, including the phase plane method, Lyapunov stability theory, numerical continuation, bifurcation analysis, and chaos theory. These methods complement one another, bridging theoretical insights with practical system behavior.

Control strategies for nonlinear electronic systems are designed to either mitigate adverse nonlinearities or leverage them to achieve desired performance. A range of control technologies has been developed for this purpose, such as feedback linearization, sliding-mode control, adaptive control, intelligent control, model predictive control, data-driven solutions, and learning-based control. These technologies balance performance, robustness, and implementation complexity, with designs tailored to specific application requirements.

The aim of this Special Issue, titled “Nonlinear Analysis and Control of Electronic Systems”, is to focus on the applications of nonlinear analysis and control in electronic systems, showcasing novel technologies and highlighting emerging trends in this research field. Submissions to this Special Issue are solicited to provide a comprehensive snapshot of the field, and both original research articles and reviews are welcome. Topics may include, but are not limited to, new devices, algorithms, solutions, and applications in the following areas:

  • Nonlinear control for EV on-board chargers;
  • Nonlinear analysis of 5G amplifier distortion;
  • Adaptive control for microgrid voltage;
  • Nonlinear modeling of Li-ion batteries;
  • Sliding-mode control for DC-DC converters;
  • Nonlinear EMI mitigation in power systems;
  • Control of LED drivers for smart lighting;
  • Nonlinear stability of IoT sensor networks;
  • Chaos suppression in power inverters;
  • Data-driven control for semiconductor devices;
  • Nonlinear fault tolerance for multi-port converters;
  • Control of off-grid solar DC-AC converters;
  • Nonlinear analysis of piezoelectric actuators;
  • Harmonic elimination with active filters;
  • DSP power optimization via nonlinear control.

We look forward to receiving your contributions.

Dr. Dianwei Qian
Prof. Dr. Shiwen Tong
Guest Editors

Manuscript Submission Information

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Keywords

  • nonlinear control
  • dynamic analysis
  • electronic systems
  • artificial intelligence

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Published Papers (3 papers)

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Research

17 pages, 1431 KB  
Article
Adaptive Multi-Sensor Fusion for Robust Outdoor Localization and Path Tracking Under Weak GNSS Conditions
by Yanyan Dai, Subin Park and Kidong Lee
Electronics 2026, 15(13), 2768; https://doi.org/10.3390/electronics15132768 - 23 Jun 2026
Viewed by 202
Abstract
Reliable outdoor localization is essential for autonomous mobile robots, where the Global Navigation Satellite System (GNSS) is widely used to provide global positioning information. However, GNSS signals are often degraded in real-world environments due to occlusions, multipath effects, and environmental interference, leading to [...] Read more.
Reliable outdoor localization is essential for autonomous mobile robots, where the Global Navigation Satellite System (GNSS) is widely used to provide global positioning information. However, GNSS signals are often degraded in real-world environments due to occlusions, multipath effects, and environmental interference, leading to unstable localization and degraded navigation performance. This paper proposes an adaptive multi-sensor fusion framework for robust outdoor localization and path tracking under weak GNSS conditions. The proposed system integrates GNSS, LiDAR, wheel odometry, and inertial measurement unit (IMU) measurements within an Extended Kalman Filter (EKF) framework. To address the limitations of GNSS, an adaptive weighting mechanism is introduced to dynamically adjust the influence of GNSS observations based on signal quality indicators. Furthermore, a GNSS quality-aware mode-switching strategy is developed, enabling seamless transition between GNSS-dominant localization and multi-sensor fusion-based localization. In the fusion mode, LiDAR, odometry, and IMU jointly provide robust pose estimation, while GNSS acts as a weak global constraint. The IMU further enhances heading estimation, improving orientation stability and path tracking performance. The estimated pose is then used for trajectory tracking using a path-following controller. Experimental results conducted in outdoor environments demonstrate that the proposed framework significantly improves localization robustness and path tracking performance under degraded GNSS conditions. Compared with raw GNSS localization, the proposed method reduces the mean localization error by 47.2% and decreases the root mean square localization error by 55.5%, while maintaining smoother and more continuous trajectory estimation in weak GNSS environments. Full article
(This article belongs to the Special Issue Nonlinear Analysis and Control of Electronic Systems)
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15 pages, 1595 KB  
Article
Vision-Guided Precision Tool Alignment and Target Contact for a Mobile Manipulator Using YOLO Detection and Depth-Based 3D Localization
by Yanyan Dai and KiDong Lee
Electronics 2026, 15(9), 1890; https://doi.org/10.3390/electronics15091890 - 29 Apr 2026
Viewed by 454
Abstract
Precision alignment and target contact are critical tasks for mobile manipulators in industrial inspection and flexible manufacturing. However, achieving high accuracy after navigation remains challenging due to accumulated errors from mobile base localization, perception noise, and calibration uncertainty. This paper proposes a vision-guided [...] Read more.
Precision alignment and target contact are critical tasks for mobile manipulators in industrial inspection and flexible manufacturing. However, achieving high accuracy after navigation remains challenging due to accumulated errors from mobile base localization, perception noise, and calibration uncertainty. This paper proposes a vision-guided precision alignment framework for mobile manipulators using a single front-facing RGB-D camera. The method integrates YOLO-based target detection, AR marker-assisted plane depth estimation, and depth-based 3D localization within a coarse-to-fine alignment strategy. After navigation, the manipulator first moves to a predefined pre-alignment pose, followed by visual localization and iterative refinement to compensate for residual errors before executing precise target contact. The proposed system is implemented and evaluated in a Gazebo-based simulation environment using a mobile manipulator platform model. In a static touch panel experiment with 50 trials, the system achieves a success rate of 98%, with positioning errors maintained within a millimeter-level range. Simulation results demonstrate that the proposed method provides stable alignment performance in the simulation environment without relying on external sensing devices such as force sensors or multi-camera systems. The proposed approach shows promising potential for precision contact tasks in mobile manipulation. Full article
(This article belongs to the Special Issue Nonlinear Analysis and Control of Electronic Systems)
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23 pages, 6133 KB  
Article
Chaos-Based Dynamical Parameter Estimation for Physical Layer Authentication in Wireless IoT Networks
by Ruslans Babajans, Darja Cirjulina, Sergejs Tjukovs, Sara Becchi, Jacopo Secco, Dmytro Vovchuk, Deniss Kolosovs and Dmitrijs Pikulins
Electronics 2026, 15(4), 748; https://doi.org/10.3390/electronics15040748 - 10 Feb 2026
Cited by 1 | Viewed by 618
Abstract
The proliferation of Internet of Things (IoT) devices and services creates not only significant benefits but also new security threats. Classical information encryption techniques are not suitable for resource-constrained edge modules, thereby generating the demand for lightweight and efficient data protection algorithms. This [...] Read more.
The proliferation of Internet of Things (IoT) devices and services creates not only significant benefits but also new security threats. Classical information encryption techniques are not suitable for resource-constrained edge modules, thereby generating the demand for lightweight and efficient data protection algorithms. This work presents a novel dynamical parameter estimation scheme for chaotic oscillators, applied to physical-layer authentication (PLA). The proposed approach relies on the receiver’s capability to estimate a selected parameter of the transmitter’s oscillator determined by circuit configuration from the received chaotic signal using a locally synchronized oscillator, thereby enabling secure authentication based on a hardware-encoded identifier. The scheme is intended to complement a chaos-based wireless sensor network (WSN) architecture, where sensor nodes (SNs) implement analog chaotic oscillators, and the gateway operates discrete-time models. The Vilnius chaotic oscillator was chosen to validate the proposed PLA scheme. A rigorous bifurcation analysis of analytical, SPICE and discrete oscillator models was first conducted to identify parameter regions that preserve chaotic dynamics, establishing correspondence between models to guarantee the feasibility of parameter estimation across implementations. The digital realization of the parameter estimator demonstrated accurate and stable operation, with a small and nearly constant estimation relative error not exceeding 1.01%. Key performance metrics were analyzed, including estimation time, precision, and noise robustness. A tradeoff between estimation speed and accuracy was identified, particularly under noisy channel conditions. Finally, the influence of the receiver’s native oscillator parameter on distinguishable transmitter parameter ranges was demonstrated, highlighting the configurability and security potential of the proposed system against unauthorized transmissions. Full article
(This article belongs to the Special Issue Nonlinear Analysis and Control of Electronic Systems)
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