A Novel Memory Filtering Design for Semi-Markovian Jump Time-Delay Systems

Wei, Yanling; Qiu, Jianbin; Karimi, Hamid Reza; Ji, Wenqiang

doi:10.1109/tsmc.2017.2759900

Cited by 100 publications

(34 citation statements)

References 45 publications

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“…So it is further hard to control this kind of process on the grounds that the time delay all the time remains alive in the measurement or control loop . A couple of novel control technologies like predictive control, the neural type of a synthetic neutral delay in a control loop to improve the control presentation . Automotive, instrumentation, motor drives are the PID controller connected in a broad range of issues .…”

Section: Introductionmentioning

confidence: 99%

“…14 A couple of novel control technologies like predictive control, 15 the neural type of a synthetic neutral delay in a control loop to improve the control presentation. 16 Automotive, instrumentation, motor drives are the PID controller connected in a broad range of issues. 17 It can anticipate the future through an imitative action and it has the capacity to eradicate steady-state offsets by means of integral action.…”

Section: Introductionmentioning

confidence: 99%

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New opposition cuttlefish optimizer based two‐step approach for optimal design of fractional order proportional integral derivative controller for time delay systems

Sumathi¹,

Umasankar²

2019

Int J Numerical Modelling

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In this article, an optimal design of the fractional order proportional integral derivative (FOPID) controller for time delay system is proposed. The proposed optimal design is the combined performance of both the cuttlefish optimizer (CFO) and Opposition-based learning (OBL) scheme called CFOBL scheme. The proposed CFOBL uses the concept of opposition based population initialization and opposition based position updating to improve its searching behavior, computational speed and convergence profile in the basic CFO. In FOPID controller, apart from the three tuning parameters (G P , G I , and G D ) there are two additional tuning parameters that are λ and μ. Here, CFOBL is used to tune the three controller parameters and also to find the optimal values of λ and μ. The uniqueness of the proposed technique is to reduce the FOPID controller's fault in the higher order time delay scheme by the aid of the controller's increase limits. The objective of the proposed technique is chosen by considering the set point parameters and the accomplished parameters from the time delay system. The proposed technique is used to avoid high-order delays and reliability constraints such as small overruns, time resolution and fixed condition defects. This technique is performed on the MATLAB/ Simulink platform and the results are compared with different existing techniques such as Ziegler-Nichols (ZN) tuning method, curve fitting (CF) technique, Wang technique, and regression technique. K E Y W O R D Scuttlefish optimizer, FOPID controller, opposition based two-step approaches, reliability constraints, time delay system

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

New opposition cuttlefish optimizer based two‐step approach for optimal design of fractional order proportional integral derivative controller for time delay systems

Sumathi¹,

Umasankar²

2019

Int J Numerical Modelling

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“…Lemma 5 (see [27,28]). For given positive integers m, n, a scalar ∈ (0, 1), and two matrices 1 ∈ S + and 2 ∈ S + .…”

Section: Problem Formulationmentioning

confidence: 99%

Improved Reduced‐Order Fault Detection Filter Design for Polytopic Uncertain Discrete‐Time Markovian Jump Systems with Time‐Varying Delays

et al. 2018

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The fault detection (FD) reduced-order filtering problem is investigated for a family of polytopic uncertain discrete-time Markovian jump linear systems (MJLSs) with time-varying delays. Under meeting the control precision requirements of the complex systems, the reduced-order fault detection filter can improve the efficiency of the fault detection. Then, by the aid of the Markovian Lyapunov function and convex polyhedron techniques, some novel time-varying delays and polytopic uncertain sufficient conditions in terms of linear matrix inequality (LMI) are proposed to insure the existence of the FD reduced-order filter. Finally, an illustrative example is provided to verify the usefulness of the given method.

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“…To facilitate the cost estimation, it is also possible to apply convex optimization algorithms [61,62] and to compare the results in future works. …”

Section: The Comparison Of the Developed Model With Other Modelsmentioning

confidence: 99%

A Model for Shovel Capital Cost Estimation, Using a Hybrid Model of Multivariate Regression and Neural Networks

et al. 2017

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Abstract:Cost estimation is an essential issue in feasibility studies in civil engineering. Many different methods can be applied to modelling costs. These methods can be divided into several main groups: (1) artificial intelligence, (2) statistical methods, and (3) analytical methods. In this paper, the multivariate regression (MVR) method, which is one of the most popular linear models, and the artificial neural network (ANN) method, which is widely applied to solving different prediction problems with a high degree of accuracy, have been combined to provide a cost estimate model for a shovel machine. This hybrid methodology is proposed, taking the advantages of MVR and ANN models in linear and nonlinear modelling, respectively. In the proposed model, the unique advantages of the MVR model in linear modelling are used first to recognize the existing linear structure in data, and, then, the ANN for determining nonlinear patterns in preprocessed data is applied. The results with three indices indicate that the proposed model is efficient and capable of increasing the prediction accuracy.

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A Novel Memory Filtering Design for Semi-Markovian Jump Time-Delay Systems

Cited by 100 publications

References 45 publications

New opposition cuttlefish optimizer based two‐step approach for optimal design of fractional order proportional integral derivative controller for time delay systems

New opposition cuttlefish optimizer based two‐step approach for optimal design of fractional order proportional integral derivative controller for time delay systems

Improved Reduced‐Order Fault Detection Filter Design for Polytopic Uncertain Discrete‐Time Markovian Jump Systems with Time‐Varying Delays

A Model for Shovel Capital Cost Estimation, Using a Hybrid Model of Multivariate Regression and Neural Networks

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