L2–L∞ Control for Delayed Singular Markov Switch System with Nonlinear Actuator Faults

Aslam, Muhammad Shamrooz

doi:10.1007/s40815-021-01102-0

Cited by 43 publications

(5 citation statements)

References 36 publications

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“…where the angle difference between truck and trailer is presented by p1(t); p2(t) is denoted by trailer's angle; and p3(t) the vertical position of the trailer's rear end is expressed. The numerical values of b, i, ī, L and v can be seen in [Table 1, [37]]. Due to the limitations of the pages, we omitted some mathematical steps.…”

Section: Resultsmentioning

confidence: 99%

Observer-Based Control for a New Stochastic Maximum Power Point Tracking for Photovoltaic Systems With Networked Control System

Aslam

Tiwari

Pandey

et al. 2023

IEEE Trans. Fuzzy Syst.

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This study discusses the new stochastic maximum power point tracking (MPPT) control approach towards the photovoltaic cells (PCs). PC generator is isolated from the grid, resulting in a direct current (DC) microgrid that can provide changing loads. In the course of the nonlinear systems through the time-varying delays, we proposed a Networked Control Systems (NCSs) beneath an event-triggered approach basically in the fuzzy system. In this scenario, we look at how random, variable loads impact the PC generator's stability and efficiency. The basic premise of this article is to load changes and the value matching to a Markov chain. PC generators are complicated nonlinear systems that pose a modeling problem. Transforming this nonlinear PC generator model into the Takagi-Sugeno (T-S) fuzzy model is another option. Takagi-Sugeno (T-S) fuzzy model is presented in a unified framework, for which 1) the fuzzy observer-based on this premise variables can be used for approximately in the infinite states to the present system, 2) the fuzzy observer-based controller can be created using this same premises be the observer, and 3) to reduce the impact of transmission burden, an event-triggered method can be investigated. Simulating in the PC generator model for the realtime climate data obtained in China demonstrates the importance of our method. In addition, by using a new Lyapunov-Krasovskii functional (LKF) for combining to the allowed weighting matrices incorporating mode-dependent integral terms, the developed model can be stochastically stable and achieves the required performances. Based on the T-P transformation, a new depiction of the nonlinear system is derived in two separate steps in which an adequate controller input is guaranteed in the first step and an adequate vertex polytope is ensured in the second step.To present the potential of our proposed method, we simulate it for PC generators.

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Section: Resultsmentioning

confidence: 99%

Observer-Based Control for a New Stochastic Maximum Power Point Tracking for Photovoltaic Systems With Networked Control System

Aslam

Tiwari

Pandey

et al. 2023

IEEE Trans. Fuzzy Syst.

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show abstract

“…Remark 3. The time-triggered mechanism-generally used in [26][27][28][29][30][31][36][37][38][39][40]42]-sends data strictly at fixed time intervals. The event-triggered mechanism used in this paper will only be triggered when the control signal used for the actuator, and the signal generated by the controller, are over a certain threshold.…”

Section: Problem Statement and Some Preliminariesmentioning

confidence: 99%

“…In practical application systems, partial component failure or sudden external interference may cause sensor faults, which will inevitably reduce the performance of the system, or even destroy the whole application system. Therefore, many scholars have been contributing to research on stochastic nonlinear control systems with sensor faults in recent years [26][27][28][29][30][31][32][33]. Xu solves the problem of generalized correntropy-filter-based fault diagnosis and fault tolerant control for stochastic nonlinear systems subject to heavy-tailed distributed noises [28].…”

Section: Introductionmentioning

confidence: 99%

“…Du discusses the problem of cooperative control for second-order, strict-feedback, stochastic, nonlinear, multi-agent systems against sensor faults [29]. Combining event-triggered mechanisms and sliding mode control, Aslam, et al investigate the complex fault control problems for Markov jump systems [30][31][32]. However, it is important to notice that the tracking performance of the above articles only ensures that the tracking error eventually converges to a neighborhood near the equilibrium point, rather than asymptotically converging to zero.…”

Section: Introductionmentioning

confidence: 99%

“…(1) An adaptive neural tracking control scheme for non-strict feedback stochastic nonlinear systems based on the event-triggered mechanism is presented. Compared with the time-triggered mechanism generally used in [26][27][28][29][30][31][36][37][38][39][40]42], this paper employs an event-triggered mechanism that reduces the frequency of control signal transmission in the system to reduce the communication burden. (2) In contrast to the normal formulation of the Lyapunov function in [34][35][36][37][38], negative exponential function is applied to the Lyapunov function to obtain exponential asymptotic tracking performance for stochastic nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Event-Triggered, Adaptive, Exponentially Asymptotic Tracking Control of Stochastic Nonlinear Systems

Cao

et al. 2022

Symmetry

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This paper investigates the problem of event-triggered, adaptive, asymptotic tracking control for a class of non-strict feedback stochastic nonlinear systems with symmetrical structures and sensor faults. Based on the negative exponential function, the event-triggered adaptive tracking control strategy deals with the problem of exponentially asymptotic convergence for the first time. The radial basis function neural network (RBFNN) mechanism addresses uncertain factors and unknown external disturbances in the system. The developed strategy ensures that all the signals of the closed-loop system are semi-globally uniformly bounded in probability, and that the tracking error can exponentially converge to zero. Finally, a simulation example demonstrates the effectiveness of the proposed method.

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A practical study of active disturbance rejection control for rotary flexible joint robot manipulator

et al. 2023

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L2–L∞ Control for Delayed Singular Markov Switch System with Nonlinear Actuator Faults

Cited by 43 publications

References 36 publications

Observer-Based Control for a New Stochastic Maximum Power Point Tracking for Photovoltaic Systems With Networked Control System

Observer-Based Control for a New Stochastic Maximum Power Point Tracking for Photovoltaic Systems With Networked Control System

Event-Triggered, Adaptive, Exponentially Asymptotic Tracking Control of Stochastic Nonlinear Systems

A practical study of active disturbance rejection control for rotary flexible joint robot manipulator

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