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Parameter Estimation of Multi‐Input Multi‐Output Hammerstein Nonlinear System With Deep GRU Networks

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A Bayesian transfer sparse identification method for nonlinear ARX systems

Zhang, K., Luan, X.-L., Ding, F., & Liu, F. (2024) · International Journal of Adaptive Control and Signal Processing · doi:10.1002/acs.3884 · Cited by 6 · see citing works

A SCRIM Drive System Using Backstepping Control and Revamped Recurrent Romanovski PNN with Mended ACO

Lin, C. (2019) · IETE Journal of Research · doi:10.1080/03772063.2019.1565956 · Cited by 5 · see citing works

An Intelligent Feedforward Controller Utilizing a Modified Gorilla Troops Optimization for Nonlinear Systems

Mahmood, T. S., & Lutfy, O. F. (2022) · Mathematical Modelling and Engineering Problems · doi:10.18280/mmep.090411 · Cited by 4 · see citing works

Semi-Supervised Incremental Soft Sensor Model With Spatiotemporal Graph Regularization for Process Industry

Li, W., Dai, W., Nan, J., & Li, B. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3500040 · Cited by 4 · see citing works

Linear Active Disturbance Rejection Control-Based Diagonal Recurrent Neural Network for Radar Position Servo Systems with Dead Zone and Friction

Cui, S., Zhu, G., & Zhao, T. (2022) · Applied Sciences · doi:10.3390/app122412839 · Cited by 4 · see citing works

Nonlinear Complex Dynamical Systems Modeling and Adaptive Control Based on a Novel Diagonally Expanded Functional Link Neural Network (DEFLNN)

Sahu, R., Kumar, R., & Srivastava, S. (2025) · Circuits Systems and Signal Processing · doi:10.1007/s00034-025-03144-3 · Cited by 3 · see citing works

An Adaptive Learning Rate Based Novel Recurrent Neural Network Modeling and Control of Complex Non‐Linear Dynamical Systems

Sahu, R., Srivastava, S., & Kumar, R. (2025) · International Journal of Adaptive Control and Signal Processing · doi:10.1002/acs.4022 · Cited by 3 · see citing works

Design of a Novel Recurrent Neural Network Model for Identification and Adaptive Control of Dynamical Systems

Rai, A., Bhushan, B., & Jaint, B. (2025) · International Journal of Robust and Nonlinear Control · doi:10.1002/rnc.70076 · Cited by 3 · see citing works

MSGM-Net: multi-scale general-modal network for disease and organ segmentation

Tan, D., Zhou, X., Jiang, C., Peng, X., Su, Y., & Zhong, W. (2025) · Complex & Intelligent Systems · doi:10.1007/s40747-025-02040-2 · Cited by 3 · see citing works

Modeling chaotic diabetes systems using fully recurrent neural networks enhanced by fractional-order learning

Mostafa, E., Mahmoud, T. A., & El-Brawany, M. A. (2025) · Scientific Reports · doi:10.1038/s41598-025-28637-8 · Cited by 3 · see citing works

Comparison of artificial neural network adaptive control techniques for a nonlinear system with delay

Guś, B., & Możaryn, J. (2023) · International Conference on Methods and Models in Automation and Robotics · doi:10.1109/mmar58394.2023.10242473 · Cited by 3 · see citing works

Convergence Analysis of Regularized Elman Neural Networks Under Relaxed Conditions

Fan, Q., Zhou, L., Zurada, J. M., Peng, J., Li, H., Wang, J., & Yang, D. (2024) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2024.3486764 · Cited by 3 · see citing works

A robust variational mode decomposition based deep random vector functional link network for dynamic system identification

Pattanaik, R. K., Rout, S. K., Sahani, M., & Mohanty, M. N. (2024) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2024.109887 · Cited by 3 · see citing works

Theoretical and experimental study of an automated kill procedure based on a neural network-PID controller

Long, Z., Yang, H., Li, J., Liu, G., Wang, C., Zhang, G., Wang, B., Zhan, J., Guan, L., Luo, M., et al. (2025) · Geoenergy Science and Engineering · doi:10.1016/j.geoen.2025.213664 · Cited by 2 · see citing works

Neural Network‐Based Adaptive Backstepping Control of Unmanned Tandem Rotor Helicopter Considering Rotor Mass Imbalance and Crosswind Disturbance

Li, W., Wang, Z., & Ren, C. (2025) · International Journal of Adaptive Control and Signal Processing · doi:10.1002/acs.4086 · Cited by 2 · see citing works

Dynamic system identification based on a novel pi-sigma neural network with Lyapunov stability analysis

Sahu, R., Kumar, R., & Srivastava, S. (2025) · ISA Transactions · doi:10.1016/j.isatra.2025.10.044 · Cited by 2 · see citing works

A hybrid framework integrating Fuzzy K-means segmentation and CNN feature extraction with SVM kernel for lung cancer classification

Ramadevi, P., & Das, R. (2026) · Evolving Systems · doi:10.1007/s12530-025-09782-x · Cited by 2 · see citing works

HCDRNN‐NMPC: A New Approach to Design Nonlinear Model Predictive Control (NMPC) Based on the Hyper Chaotic Diagonal Recurrent Neural Network (HCDRNN)

Johari, S., Yaghoobi, M., & Kobravi, H. R. (2022) · Complexity · doi:10.1155/2022/1006197 · Cited by 2 · see citing works

A novel locally connected recurrent neural network for identification of nonlinear dynamical system

Shobana, R., Kumar, R., & Jaint, B. (2023) · International Conference on Signal Processing and Integrated Networks (SPIN) · doi:10.1109/spin57001.2023.10117315 · Cited by 2 · see citing works

Modelling of a Non-Linear Dynamic System Using Long Short-Term Memory

Sahu, R., Srivastava, S., & Kumar, R. (2023) · International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) · doi:10.1109/icccis60361.2023.10425027 · Cited by 2 · see citing works

Joint data augmentations for automated graph contrastive learning and forecasting

Liu, J., Chen, Y., Ren, Q., & Gao, Y. (2024) · Complex & Intelligent Systems · doi:10.1007/s40747-024-01491-3 · Cited by 2 · see citing works

Advancing nonlinear dynamics identification with recurrent quantum neural networks: Emphasizing Lyapunov stability and adaptive learning in system analysis

Shaheen, O., Elshazly, O., Baihan, A., El‐Shafai, W., & Khalil, H. (2024) · Alexandria Engineering Journal · doi:10.1016/j.aej.2024.09.066 · Cited by 2 · see citing works

Model-Free and Pseudoinverse-Free Zhang Neurodynamics Scheme for Robotic Arms’ Path Tracking Control

Chen, J., Pan, Y., & Zhang, Y. (2025) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2025.3540589 · Cited by 2 · see citing works

Advancing Arabic Sign Language Recognition: A Novel MobileNetv2-Based DL Framework with Superior Accuracy and Cross-Dataset Validation

Mamlook, R. E. A., & Aljohani, A. A. (2025) · Arabian Journal for Science and Engineering · doi:10.1007/s13369-025-10528-9 · Cited by 2 · see citing works

Transformation Method of Nonlinear Mathematical Models of the DC Series Drive into the Form of Modified Recurrent Neural Network

Orlovskyi, I. (2019) · Canadian Journal of Electrical and Computer Engineering · doi:10.1109/cjece.2018.2885855 · Cited by 2 · see citing works

A Novel Approach for Predicting the Compressive and Flexural Strength of Steel Slag Mixed Concrete Using Feed-Forward Neural Network

Gupta, T., & Sachdeva, S. N. (2020) · Lecture notes in mechanical engineering · doi:10.1007/978-981-15-5463-6_41 · Cited by 2 · see citing works

Diagonal Recurrent Neural Network Based Prediction Model for Sales Forecasting

Tiwari, R., Kumar, R., Srivastava, S., & Gera, R. (2020) · Studies in computational intelligence · doi:10.1007/978-981-15-7571-6_29 · Cited by 2 · see citing works

Controller design for an approximated nonlinear system using Wavelet Transform

Pathak, R. R., Sengupta, A., Paul, R., & Mondal, U. (2025) · ISA Transactions · doi:10.1016/j.isatra.2025.07.030 · Cited by 1 · see citing works

Neuro-Fuzzy Non-linear Controller with Deep Reinforcement Learning

Hien, D. T., & Nguyen, T.-L. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-032-03856-2_44 · Cited by 1 · see citing works

Vibration control of electromagnetic suspensions based on self-sensing position estimation and hierarchical control framework

An, Q., Lai, J., Wang, S., Zhang, B., Tan, B., Ning, D., Du, H., & He, Y. (2025) · International Journal of Dynamics and Control · doi:10.1007/s40435-025-01948-4 · Cited by 1 · see citing works

A hybrid learning algorithm for locally recurrent neural networks

Varsamis, D., Outsios, E., & Mastorocostas, P. (2018) · Contemporary Engineering Sciences · doi:10.12988/ces.2018.711194 · Cited by 1 · see citing works

The nonlinear Choke Parameter Identification based on the Modified Artificial Neural Network

Orlovskyi, I., & Fajfer, M. (2020) · 2020 IEEE Problems of Automated Electrodrive. Theory and Practice (PAEP) · doi:10.1109/paep49887.2020.9240877 · Cited by 1 · see citing works

A New Method of Applying Data Engine Technology to Realize Neural Network Control

Zheng, S., Bi, C., & Song, Y. (2019) · Algorithms · doi:10.3390/a12050097 · Cited by 1 · see citing works

Distributed Consensus Control for Nonlinear Multi-agent Systems

Chen, X., Wu, M., Pedrycz, W., Gałkowski, K., & Paszke, W. (2021) · Studies in systems, decision and control · doi:10.1007/978-3-030-62147-6_8 · Cited by 1 · see citing works

Decoupling Control for a Class of Dynamic Nonlinear Coupling Systems via ADRC based on DRNN

Ni, C., & Zhao, T. (2020) · Chinese Control and Decision Conference (CCDC) · doi:10.1109/ccdc49329.2020.9164477

Feedback error learning neural network for stable control of nonlinear nonaffine systems

Asgari, M., & Asgari, M. (2022) · Transactions of the Institute of Measurement and Control · doi:10.1177/01423312221086076

Adaptive Event-Triggered Neural Network Fast Finite-Time Control for Uncertain Robotic Systems

Wang, J., Du, Y., Zhang, Y., Gu, Y., & Chen, K. (2023) · Mathematics · doi:10.3390/math11234841

An Input Context Layered Local Recurrent Neural Network for Nonlinear System Identification

Shobana, R., Kumar, R., & Jaint, B. (2024) · IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems · doi:10.1109/icpeices62430.2024.10719117

Reconfigurable Neuromorphic Neural Network Architecture

Sharma, K., Sarangi, P. K., Sharma, P., Nayak, S. R., Aluvala, S., & Swain, S. K. (2024) · Applied Computational Intelligence and Soft Computing · doi:10.1155/2024/6632801

Moor: Model-based offline policy optimization with a risk dynamics model

Su, X., Li, P., & Chen, S. (2024) · Complex & Intelligent Systems · doi:10.1007/s40747-024-01621-x

Robust Fault-Tolerant Hybrid Tracking Controller Design for Rudderless Flying-Wing UAVs with Nonlinear Dynamics

Movahhed, S. R., & Hamed, M. A. (2025) · Arabian Journal for Science and Engineering · doi:10.1007/s13369-025-10504-3

Model Reference Adaptive Method for Satellite Attitude Tracking Control

DeQing, L., Li, X., Yanghao, L., & Chao, Z. (2025) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2025.11.307

Actor-Critic Reinforcement Learning-Based Active Disturbance Rejection Control for Mobile RobotsPreprint

Fareh, R., Habib, U., El-Nagar, A. M., Khadraoui, S., & Bettayeb, M. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5900062

Decentralised and Centralised Fixed Structure H ∞ Robust Loop Shaping for the MIMO Microsurgical Manipulation Based on PSOGSA

Kaitwanidvilai, S., Konghuayrob, P., & Aoyama, H. (2026) · IET Control Theory and Applications · doi:10.1049/cth2.70086

Trend-Aware-Based Type-2 Vector Fuzzy Neural Network for Nonlinear System Identification

Sun, C., Fang, F., Wu, X., & Han, H. (2026) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2026.3658516

A hybrid parallel decomposed interval type-2 fuzzy-Jordan neural network for controlling uncertain ball-and-beam systems

Hùng, N. M., Ho, V. H., & Le, T.-L. (2026) · Physica Scripta · doi:10.1088/1402-4896/ae442b

Hybrid Deep Learning Control of the Electrohydraulic Servodrive Position for the Repetitive Task

Guś, B., Możaryn, J., & Winnicki, A. (2026) · International Journal of Robust and Nonlinear Control · doi:10.1002/rnc.70472

Decentralized Adaptive Safe Voltage-Tracking Constrained Control for DC Microgrid Systems with Constant Power Loads

Zhu, L., Yong Ge, L. I. U., & Zhu, Y. (2026) · International Journal of Control Automation and Systems · doi:10.1007/s12555-026-00035-4

Enhancing Reference Tracking in Induction Motor Drives: A Hybrid Model Predictive Control and Artificial Neural Network Approach

del Rio, A., Barambones, Ó., Artetxe, E., Uralde, J., & Calvo, I. (2026) · International Journal of Robust and Nonlinear Control · doi:10.1002/rnc.70609

Robust Identification Algorithm of Network Communication Signals via Machine Learning Model

Fan, X., Zhou, L., Yu, W., & Sun, P. (2026) · Automatic Control and Computer Sciences · doi:10.3103/s0146411626700112

A deterioration classification framework for insulators using metaheuristic optimization and hybrid machine learning

Thanh, P. N. (2026) · Evolving Systems · doi:10.1007/s12530-026-09851-9

Diagonal recurrent neural networks for control of dynamic systems

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Diagonal recurrent neural network-based control: convergence and stability

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Diagonal recurrent neural networks for dynamic systems control

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Diagonal recurrent neural network based identification of nonlinear dynamical systems with Lyapunov stability based adaptive learning rates

Kumar, R., Srivastava, S., Gupta, J. R. P., & Mohindru, A. (2018) · Neurocomputing · doi:10.1016/j.neucom.2018.01.073 · Cited by 70 · see citing works

Diagonal recurrent neural network based control using adaptive learning rates

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