An Extended Synchronization Method to Identify Slowly Time-Varying Parameters in Nonlinear Systems

Zhang, Xiaoxu; Xu, Jian

doi:10.1109/tsp.2017.2770092

Cited by 9 publications

(5 citation statements)

References 31 publications

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“…As seen in Figure 2(A), it is evident that system state x DD2 generated by the DD method fluctuates greatly during the runtime. From Figures 2(B) through 2(C), DD2 controller (21) and the optimal output do not achieve the desired results. Moreover, absolute residual errors |e DD2 | are larger than zero.…”

Section: T)mentioning

confidence: 92%

“…It can be concluded that the DD method can not solve the output optimization of STVN system (20). The reason for this may be that in order to obtain DD2 controller (21), the 2nd-order time derivative of the gradient function needs to be operated. Since the actual error is always nonzero (approximately zero), the errors accumulation in the calculation will become large.…”

Section: T)mentioning

confidence: 99%

“…Thus, the influence of the perturbation on the DD method can not be ignored. Besides, DD2 controller (21) in the form of . u may introduce the other errors, which also affects the performance of the DD method.…”

Section: T)mentioning

confidence: 99%

“…With the development of science and technology, the subjects of research have become complicated [10]. Meanwhile, the requirements for the stability and accuracy of the systems are getting higher and higher [20][21][22][23]. Since the time-varying and nonlinear systems are more suitable for the actual physical systems than the simple systems, the systems with the nonlinear or time-varying or both characteristics are considered in [3,6,8].…”

Section: Introductionmentioning

confidence: 99%

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Output optimization of scalar and 2‐dimension time‐varying nonlinear systems using zeroing dynamics

Zhang

Shi

Yang

et al. 2020

Asian Journal of Control

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The optimal control of time-varying nonlinear systems is an important research topic and faces many difficulties and challenges, but also has substantial benefits. In this paper, the output optimization of scalar time-varying nonlinear (STVN) system and 2-dimension time-varying nonlinear (2DTVN) system is considered. The zeroing dynamics (ZD) method, which can solve the time-varying problems flexibly and effectively, has been extensively used in recent years. By introducing the ZD method, the time-varying optimal system state is attained, and the controller with the optimal output is designed. Meanwhile, the direct dynamics (DD) method is presented to further illustrate the superiority of the ZD method. Theoretical analyses prove that the ZD method has a faster convergence rate (that is, exponential convergence). In addition, the effectiveness and feasibility of the ZD method for solving the output optimization of STVN and 2DTVN systems are verified by numerical experiments, and further substantiated via output optimization of a two-wheeled mobile robot.

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Section: T)mentioning

confidence: 92%

Section: T)mentioning

confidence: 99%

Section: T)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Output optimization of scalar and 2‐dimension time‐varying nonlinear systems using zeroing dynamics

Zhang

Shi

Yang

et al. 2020

Asian Journal of Control

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“…Researchers have made valuable attempts in the theoretical analysis and derivation of unknown parameters. [6][7][8][9][10] Commonly, some parameter identification algorithms have been proposed based on the system's input and output. The algorithms for parameter identification of linear time-invariant (LTI) or linear slowvarying (LSV) systems have been relatively mature.…”

Section: Introductionmentioning

confidence: 99%

Time-varying structural parameter identification for the offshore gangway

Xu,

Yang,

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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The offshore gangway is a new type of offshore transfer equipment, equivalent to an offshore passage. This device makes it convenient for people to transfer between a vessel and an offshore structure. The control algorithm of the gangway system demands adjusting its control parameters to deal with harsh sea conditions and ensure personnel safety. Thence, it is essential to foreknow its time-varying structural parameters, such as the moment of inertia, the mass, the location of the mass center, and so on. However, due to the highly complex structure, these parameters are difficult to obtain through measurement directly. To adaptively identify these time-varying parameters for better controller design, this paper proposes a novel structural parameter identification approach based on the idea of interval division. During the identification process, the entire period is uniformly divided into several intervals. The time-varying model of the offshore gangway system can be represented in each interval by a quadratic regression equation, the coefficients of which can be derived by the least-squares algorithm. Furthermore, to adapt to the different variation frequencies and amplitudes of the parameters, the divided intervals are of distinct sizes according to the characteristics of each identification parameter. In addition, the particle swarm algorithm is employed to obtain the optimal interval sizes, the cost function of which consists of a series of output error terms. Verified by simulation, the method presented in this paper can effectively estimate the structural parameters of the offshore gangway with high accuracy, with mean square errors reduced by at least 2/3 compared to other methods proposed in previous research.

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Constrained particle swarm optimization for health maintenance in three-mass resonant servo control system with LuGre friction model

et al. 2021

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An Extended Synchronization Method to Identify Slowly Time-Varying Parameters in Nonlinear Systems

Cited by 9 publications

References 31 publications

Output optimization of scalar and 2‐dimension time‐varying nonlinear systems using zeroing dynamics

Output optimization of scalar and 2‐dimension time‐varying nonlinear systems using zeroing dynamics

Time-varying structural parameter identification for the offshore gangway

Constrained particle swarm optimization for health maintenance in three-mass resonant servo control system with LuGre friction model

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