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Second-order optimization methods for time-delay Autoregressive eXogenous models: Nature gradient descent method and its two modified methods (2022)
Journal Article
Chen, J., Pu, Y., Guo, L., Cao, J., & Zhu, Q. (2023). Second-order optimization methods for time-delay Autoregressive eXogenous models: Nature gradient descent method and its two modified methods. International Journal of Adaptive Control and Signal Processing, 37(1), 211-223. https://doi.org/10.1002/acs.3519

This article proposes several second-order optimization methods for time-delay ARX model. Since the time-delay in the information vector makes the traditional identification algorithms be inefficient, a redundant rule based method is utilized to tran... Read More about Second-order optimization methods for time-delay Autoregressive eXogenous models: Nature gradient descent method and its two modified methods.

Greedy search method for separable nonlinear models using stage Aitken gradient descent and least squares algorithms (2022)
Journal Article
Chen, J., Mao, Y., Gan, M., Wang, D., & Zhu, Q. (2023). Greedy search method for separable nonlinear models using stage Aitken gradient descent and least squares algorithms. IEEE Transactions on Automatic Control, 68(8), 5044-5051. https://doi.org/10.1109/TAC.2022.3214474

Aitken gradient descent (AGD) algorithm takes some advantages over the standard gradient descent (SGD) and Newton methods: (1) can achieve at least quadratic convergence in general; (2) does not require the Hessian matrix inversion; (3) has less comp... Read More about Greedy search method for separable nonlinear models using stage Aitken gradient descent and least squares algorithms.

U-Model-Based adaptive sliding mode control using a deep deterministic policy gradient (2022)
Journal Article
Lei, C., & Zhu, Q. (2022). U-Model-Based adaptive sliding mode control using a deep deterministic policy gradient. Mathematical Problems in Engineering, 2022, 1-14. https://doi.org/10.1155/2022/8980664

This paper presents a U-model-based adaptive sliding mode control (SMC) using a deep deterministic policy gradient (DDPG) for uncertain nonlinear systems. The configuration of the proposed methodology consisted of a U-model framework and an SMC with... Read More about U-Model-Based adaptive sliding mode control using a deep deterministic policy gradient.

Modified multi-direction iterative algorithm for separable nonlinear models with missing data (2022)
Journal Article
Chen, J., Hu, M., Mao, Y., & Zhu, Q. (2022). Modified multi-direction iterative algorithm for separable nonlinear models with missing data. IEEE Signal Processing Letters, 29, 1968-1972. https://doi.org/10.1109/LSP.2022.3204408

Multi-direction iterative (MUL-DI) algorithm is an efficient algorithm for large-scale models, and it establishes a theoretical linkage between least squares (LS) and gradient descent (GD) algorithms. However, it involves Givens transformation and de... Read More about Modified multi-direction iterative algorithm for separable nonlinear models with missing data.

Hierarchical multi-innovation stochastic gradient identification algorithm for estimating a bilinear state-space model with moving average noise (2022)
Journal Article
Gu, Y., Dai, W., Zhu, Q., & Nouri, H. (2023). Hierarchical multi-innovation stochastic gradient identification algorithm for estimating a bilinear state-space model with moving average noise. Journal of Computational and Applied Mathematics, 420, 114794. https://doi.org/10.1016/j.cam.2022.114794

This paper considers the combined parameter and state estimation problem of a bilinear state space system with moving average noise. There are product terms of state variables and control variables in bilinear systems, which brings difficulties to pa... Read More about Hierarchical multi-innovation stochastic gradient identification algorithm for estimating a bilinear state-space model with moving average noise.

Robust adaptive dynamic surface control scheme for a class of single‐input and single‐output uncertain nonlinear systems in strict‐feedback form (2022)
Journal Article
Soukkou, Y., Tadjine, M., Nibouche, M., & Zhu, Q. (2022). Robust adaptive dynamic surface control scheme for a class of single‐input and single‐output uncertain nonlinear systems in strict‐feedback form. International Journal of Adaptive Control and Signal Processing, 36(11), 2938-2952. https://doi.org/10.1002/acs.3486

This article presents a robust adaptive dynamic surface control using σ-modification adaptation laws for a class of single-input and single-output (SISO) uncertain nonlinear systems in strict-feedback form with parametric uncertainties and external d... Read More about Robust adaptive dynamic surface control scheme for a class of single‐input and single‐output uncertain nonlinear systems in strict‐feedback form.

An improved U-control design for nonlinear systems represented by input/output differential models with a disturbance observer (2022)
Journal Article
Li, R., Zhu, Q., Zhang, W., Yue, X., & Narayan, P. (2023). An improved U-control design for nonlinear systems represented by input/output differential models with a disturbance observer. International Journal of Control, 96(11), 2737-2748. https://doi.org/10.1080/00207179.2022.2111370

This paper presents a new method to calculate the inversion of the controlled linear/nonlinear dynamic plants which are described by input–output differential equation models. This new U-model-based inverter (U-inverter), cancels both system dynamics... Read More about An improved U-control design for nonlinear systems represented by input/output differential models with a disturbance observer.

A comprehensive expectation identification framework for multirate time-delayed systems (2022)
Journal Article
Chen, J., Gao, J., Liu, Y., Wang, C., & Zhu, Q. (2023). A comprehensive expectation identification framework for multirate time-delayed systems. IEEE Transactions on Industrial Informatics, 19(5), 7011-7021. https://doi.org/10.1109/TII.2022.3194656

The expectation maximization (EM) algorithm has been extensively used to solve system identification problems with hidden variables. It needs to calculate a derivative equation and perform a matrix inversion in the EM-M step. The equations related to... Read More about A comprehensive expectation identification framework for multirate time-delayed systems.

Least square algorithm based on bias compensated principle for parameter estimation of canonical state space model (2022)
Journal Article
Liu, L., Long, Z., Azar, A. T., Zhu, Q., Ibraheem, I. K., & Humaidi, A. J. (2022). Least square algorithm based on bias compensated principle for parameter estimation of canonical state space model. Measurement and Control, 55(5-6), https://doi.org/10.1177/00202940211064179

Due to the existence of system noise and unknown state variables, it is difficult to realize unbiased estimation with minimum variance for the parameter estimation of canonical state space model. This paper presents a new least squares estimator base... Read More about Least square algorithm based on bias compensated principle for parameter estimation of canonical state space model.

Adaptive fixed-time neural networks control for pure-feedback non-affine nonlinear systems with state constraints (2022)
Journal Article
Li, Y., Zhu, Q., Zhang, J., & Deng, Z. (2022). Adaptive fixed-time neural networks control for pure-feedback non-affine nonlinear systems with state constraints. Entropy, 24(5), 737. https://doi.org/10.3390/e24050737

A new fixed-time adaptive neural network control strategy is designed for pure-feedback non-affine nonlinear systems with state constraints according to the feedback signal of the error system. Based on the adaptive backstepping technology, the Lyapu... Read More about Adaptive fixed-time neural networks control for pure-feedback non-affine nonlinear systems with state constraints.

Robust variable-step perturb-and-observe sliding mode controller for grid-connected wind-energy-conversion systems (2022)
Journal Article
Toumi, I., Meghni, B., Hachana, O., Azar, A. T., Boulmaiz, A., Humaidi, A. J., …Bahgaat, N. K. (in press). Robust variable-step perturb-and-observe sliding mode controller for grid-connected wind-energy-conversion systems. Entropy, 24(5), 731. https://doi.org/10.3390/e24050731

In order to extract efficient power generation, a wind turbine (WT) system requires an accurate maximum power point tracking (MPPT) technique. Therefore, a novel robust variable-step perturb-and-observe (RVS-P&O) algorithm was developed for the machi... Read More about Robust variable-step perturb-and-observe sliding mode controller for grid-connected wind-energy-conversion systems.

A new configuration of composite nonlinear feedback control for nonlinear systems with input saturation (2022)
Journal Article
Zhu, Q., Mobayen, S., Nemati, H., Zhang, J., & Wei, W. (2023). A new configuration of composite nonlinear feedback control for nonlinear systems with input saturation. Journal of Vibration and Control, 29(5-6), 1417-1430. https://doi.org/10.1177/10775463211064010

This study proposes a U-control–based Composite Nonlinear Feedback (U-CNF) design procedure. This U-CNF control establishes a double feedback loop framework for generalisation and simplification in designing the CNF control systems. Two controllers,... Read More about A new configuration of composite nonlinear feedback control for nonlinear systems with input saturation.