A robust predictive observer-based integral control law for uncertain LTI systems under external disturbance

Ghaffari, Valiollah

doi:10.1016/j.jfranklin.2022.06.037

Cited by 8 publications

(2 citation statements)

References 42 publications

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“…The discrete-time situation and the continuous-time case have each been studied in [16][17][18] in turn. The set-valued estimating technique seeks to construct ellipsoids around state estimations that are both consistent with the observations and subject to particular norm constraints with regard to the noise disturbances [19].…”

Section: ░ 2 Literature Reviewmentioning

confidence: 99%

SCSO-MHEF: Sand Cat Swarm Optimization based MHEF for Nonlinear LTI-IoT Sensor Data Enhancement

Bashir,

Queen,

Habib

2024

IJEER

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Sensor data is an integral component of internet of things (IoT) and edge computing environments and initiatives. In IoT, almost any entity imaginable can be outfitted with a unique identifier and the capacity to transfer data over a network. The estimate problem was formulated as a min-max problem subject to system dynamics and limitations on states and disturbances within the moving horizon strategy framework. In this paper, a novel Sand Cat Swarm Optimization Based MHEF for Nonlinear LTI IOT Sensor Data Enhancement (SCSO-MHEF) is proposed. In the proposed method the MHEF is optimized using Sand Cat Swarm Optimization to enhance sensor data stability tuned by initial parameters. Simulation experiments were conducted on various and unique scenarios in various orders LTI system with IOT sensor data in order to validate the suggested approach. This method can be used to analyze systems with dynamically changing systems. The proposed SCSO-MHEF technique overall accuracy of 84.5%, 87.3 %, and 99.5 % better than Kalman Filter (KF), EKF and Moving Horizon Filter (MHEF) respectively.

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Section: ░ 2 Literature Reviewmentioning

confidence: 99%

SCSO-MHEF: Sand Cat Swarm Optimization based MHEF for Nonlinear LTI-IoT Sensor Data Enhancement

Bashir,

Queen,

Habib

2024

IJEER

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“…Thus, the integral controller would be found when closed-loop stability is guaranteed. Lately, some systematic frameworks have been developed for designing integral control in uncertain LTI systems (Ghaffari, 2020a(Ghaffari, , 2022. In recent years, several CNF controllers have been developed aiding sliding-model control (SMC).…”

Section: Introductionmentioning

confidence: 99%

Observer-based integral controller using composite nonlinear feedback for saturated control systems

Ghaffari

Vazani

2023

Transactions of the Institute of Measurement and Control

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Usually, simultaneous improvement of the transient performance and static accuracy is a challenging issue in saturated control systems. Employing an observer and the concept of composite nonlinear feedback, an integral controller is developed for constrained continuous-time systems. To achieve the control goal in the regulation purpose, a linear model is first derived by linearization about the operating point. Some parameters of the integral control are adjusted via the feedback passivation idea. The integral control law would be presented when a passivity condition is satisfied. Adding suitable damping terms to the existing one, the final controller is modified to enhance the response quality of the closed-loop system. The obtained results are evaluated in some numerical real examples. Although such a control method uses linearization, the outcomes of simulations, as well as the calculated performance indexes, discover the efficiency of the designed control system over the comparable ones.

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Dissipativity-based asynchronous control for time-varying delay T–S fuzzy Markov jump systems with multisource disturbances and input saturation

Guo,

Ma,

et al. 2023

Int. J. Mach. Learn. & Cyber.

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A robust predictive observer-based integral control law for uncertain LTI systems under external disturbance

Cited by 8 publications

References 42 publications

SCSO-MHEF: Sand Cat Swarm Optimization based MHEF for Nonlinear LTI-IoT Sensor Data Enhancement

SCSO-MHEF: Sand Cat Swarm Optimization based MHEF for Nonlinear LTI-IoT Sensor Data Enhancement

Observer-based integral controller using composite nonlinear feedback for saturated control systems

Dissipativity-based asynchronous control for time-varying delay T–S fuzzy Markov jump systems with multisource disturbances and input saturation

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