Application of fuzzy adaptive control to a MIMO nonlinear time-delay pump-valve system

Lai, Zhounian; Wu, Peng; Wu, Dazhuan

doi:10.1016/j.isatra.2015.01.010

Cited by 12 publications

(10 citation statements)

References 20 publications

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“…In addition to that, the nominal system (7) is reconstructed into the following form by the incorporation of time‐varying input delay into account:

\begin{align} {\overset{ζ}{true}}_{w i} false(t false) & = A_{w} ζ_{w i} false(t false) + B_{w} f false(ζ_{w i} false(t false) false) + C_{w} û_{i} false(t prefix- d false(t false) false) + a true \sum_{j = 1}^{n} G_{i j} H ζ_{w i} false(t false), \\ z_{w i} false(t false) & = D_{w} ζ_{w i} false(t false), \end{align}

where

ζ_{w i} (t)

and

z_{w i} (t)

represent the state and output vector of the nominal system with input delay and

A_{w}

B_{w}

C_{w}

, and

D_{w}

denote the given coefficient matrices with suitable dimensions. It should be mentioned that in the existing literatures (see References 29‐32), the ESP‐based approach is widely used to compensate and reject the delay phenomenon in control input channel. As a follow‐up, the state space representation of ESP is given by

\begin{align} {\overset{ζ}{true}}_{e i} false(t false) ... \end{align}

…”

Section: Problem Formulationmentioning

confidence: 99%

“…Thus, the SP approach is developed as an extended Smith predictor (ESP) approach by incorporating the main feedback path in the conventional SP block. 32 With the use of ESP technique, the controller performances are enhanced with respect to both the time-dependent and independent input delays. Generally, the states of the system are measured with the aid of sensors.…”

Section: Introductionmentioning

confidence: 99%

“…Although, it cannot achieve productive performances ahead the time‐varying input delays. Thus, the SP approach is developed as an extended Smith predictor (ESP) approach by incorporating the main feedback path in the conventional SP block 32 . With the use of ESP technique, the controller performances are enhanced with respect to both the time‐dependent and independent input delays.…”

Section: Introductionmentioning

confidence: 99%

“…Prompted by the earlier discussions, this study portraits the robust asymptotic synchronization problem of CDNs with nonlinearities, parametric uncertainties, disturbances, and time‐varying input delay. Precisely, inspired by the works in References 29‐32, an ESP‐based dynamic output feedback control law is designed for CDNs to fulfill the above mentioned research gap. Especially, an output of the IEIDE is incorporated in control protocol to enhance the control performance since it rejects the effect of unpredictable factors without any prior knowledge of them.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Disturbance estimation and synchronization control design for nonlinear complex dynamical networks with input delays

Sakthivel

Harshavarthini

Kwon

2022

Intl J Robust & Nonlinear

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The synchronization problem of complex dynamical networks (CDNs) with nonlinearities, uncertainties, time-varying input delays and disturbances is investigated in this article. The key objective of this work is to estimate both the matched and mismatched disturbance signals, which is accomplished by making use of improved-equivalent-input-disturbance estimator (IEIDE) technique. Subsequently, the impact of time-delays in control input can be effectively handled by means of extended Smith predictor (ESP) approach. To be precise, an unified dynamic output feedback control protocol is developed for dealing the disturbances and input delays by combining IEIDE and ESP strategy for nonlinear CDNs. Moreover, Lyapunov stability theory is utilized for the resultant closed-loop system to deduce the linear matrix inequality (LMI)-based sufficient stability conditions, which ensure the asymptotic synchronization of the considered system. In addition, the unpredictable disturbance signals are estimated with high precision based on the proposed control design. More precisely, the desired gain matrices are obtained by solving the LMI-based conditions. In the final analysis, the simulation results of the Lur'e system are provided to examine the practicability and efficacy of the developed control strategy.

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“…In addition to that, the nominal system (7) is reconstructed into the following form by the incorporation of time‐varying input delay into account:

\begin{align} {\overset{ζ}{true}}_{w i} false(t false) & = A_{w} ζ_{w i} false(t false) + B_{w} f false(ζ_{w i} false(t false) false) + C_{w} û_{i} false(t prefix- d false(t false) false) + a true \sum_{j = 1}^{n} G_{i j} H ζ_{w i} false(t false), \\ z_{w i} false(t false) & = D_{w} ζ_{w i} false(t false), \end{align}

where

ζ_{w i} (t)

and

z_{w i} (t)

represent the state and output vector of the nominal system with input delay and

A_{w}

B_{w}

C_{w}

, and

D_{w}

\begin{align} {\overset{ζ}{true}}_{e i} false(t false) ... \end{align}

…”

Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Disturbance estimation and synchronization control design for nonlinear complex dynamical networks with input delays

Sakthivel

Harshavarthini

Kwon

2022

Intl J Robust & Nonlinear

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show abstract

“…Also, this architecture cannot affect network induced delay. It is important to note that apart from communication over computer networks, there are others factors, which contribute towards delays [29][30][31]. Such delays should not be confused with network induced delays when testing performance of a control system over a computer network or the internet.…”

Section: Model and Assumptionsmentioning

confidence: 99%

A multi-threaded communication architecture for networked control systems

Syed

2019

NUST J. Eng. Sci.

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Advancement in communication technology has paved the way for geographically dislocating controllers from the plants they are controlling. Establishing a secure and reliable communication is an essential component to achieve robust control performance. Myriad network control schemes have been proposed but they are incapacitated due to a lack of reliable software paradigm. This highlights the need of a distributed system, which provides platform for smooth communication between a plant and its controller. In this work, we propose CASAPAC, which is a multi-threaded communication architecture designed to ensure reliable and in-order delivery of information between different modules of a network control system. Any control algorithm can be tested and employed over any network using CASAPAC. An adaptive fuzzy controller and a network based gain scheduled PI (Proportional Integral) controller have been tested on different networks using CASAPAC. In both cases, tests were carried out on a real plant of a coupled tank system. CASAPAC was able to handle all the communication efficiently in different scenarios and good control performance was achieved in both cases.

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Tracking control design for cyber‐physical systems with disturbances and input delays: An interval type‐2 fuzzy approach

Sakthivel,

Anusuya,

Kong

et al. 2024

Adaptive Control & Signal

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SummaryThe underlying intention of this work is to devise a tracking control protocol for the nonlinear cyber‐physical systems that are prone to external disturbances, time‐varying input delays and deception attacks. To be more precise, the modified repetitive tracking controller is formulated for ensuring the asymptotic tracking outcomes of the assayed system with the aim of addressing the impacts caused by external disturbances as well as input time‐varying delays. First of all, the nonlinearities of the investigated cyber‐physical systems are efficaciously approximated by the interval type‐2 fuzzy model approach. Further, the predictor technique is utilized in this study to mitigate the influence of input delays and specifically, the extended Smith predictor approach is employed. That is, the transfer function is inserted into the conventional Smith predictor's main feedback channel. In parallel, the active disturbance rejection technique is executed to reject and estimate the external disturbance impacts on the assayed system. Notably, the improved equivalent‐input‐disturbance estimator approach is tied up and more precisely, the estimated disturbances obtained from the afore‐said estimator are incorporated into the proposed controller. Whilst the deception attacks are characterized as a stochastic distributed random variable that are governed by the Bernoulli distribution. With all of this as a backdrop, the appropriate delay‐dependent constraints are expressed in the context of linear matrix inequalities by employing the Lyapunov stability theory. In line with the predetermined criteria, the relations for computing the required gain matrices are also formulated. Ultimately, the simulation analysis is carried out using two distinct numerical examples to confirm the importance of the proposed control mechanism from the perspective of theory as well as practice.

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Application of fuzzy adaptive control to a MIMO nonlinear time-delay pump-valve system

Cited by 12 publications

References 20 publications

Disturbance estimation and synchronization control design for nonlinear complex dynamical networks with input delays

Disturbance estimation and synchronization control design for nonlinear complex dynamical networks with input delays

A multi-threaded communication architecture for networked control systems

Tracking control design for cyber‐physical systems with disturbances and input delays: An interval type‐2 fuzzy approach

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