Adaptive Sliding-Mode Control of Markov Jump Nonlinear Systems With Actuator Faults

Li, Hongyi; Shi, Peng; Yao, Deyin

doi:10.1109/tac.2016.2588885

Cited by 360 publications

(158 citation statements)

References 15 publications

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“…Therefore, the research on reducing the energy consumption of injection molding machine is in line with the requirements of green production. In research [40][41][42], the control strategy of hydraulic system in injection molding process is basically controlled by fuzzy sliding mode control (FSMC). This control strategy can force the control system to slide according to the predetermined state of sliding mode according to the current state of the control system in dynamic process.…”

Section: Injection Machine Parametersmentioning

confidence: 99%

Energy-Efficient Enhancement for Viscoelastic Injection Rheomolding Using Hierarchy Orthogonal Optimization

Wang

Zhang

2018

Mathematical Problems in Engineering

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The viscoelastic injection molding involves multidisciplinary thermoplastic rheomolding parameters which is a complex mathematical problem. Particularly for rheomolding of complex parts with thin-walled structure, boss, and grooves, the increasing higher requirements on energy efficiency and rheomolding quality are put forward. Therefore, an energy-efficient enhancement method for viscoelastic injection molding using hierarchy orthogonal optimization (HOO) is proposed. Based on the thermoplastic rheomolding theory and considering the viscoelastic effects in injection molding, a set of partial differential equations (PDE) describing the physical coupling behavior of the mold-melt-injection molding machine is established. The fuzzy sliding mode control (FSMC) is used to reduce the energy consumption in the control system of the injection molding machine's clamping force. Then, the HOO model of viscoelastic injection rheomolding is built in terms of thermoplastic rheomolding parameters and injection machine parameters. In initial hierarchy, through Taguchi orthogonal experiment and Analysis of Variance (ANOVA), the amount of gate, melt temperature, mold temperature, and packing pressure are extracted as the significant influence parameters. In periodical hierarchy, the multiobjective optimization model takes the forming time, warping deformation, and energy consumption of injection molding as the multiple objectives. The NSGA-II (Nondominated Sorting Genetic Algorithm II) optimization is employed to obtain the optimal solution through the global Pareto front. In ultimate hierarchy, three candidate schemes are compared on multiple objectives to determine the final energy-efficient enhancement scheme. A typical temperature controller part is analyzed and the energy consumption of injection molding is reduced by 41.85%. Through the physical experiment of injection process, the proposed method is further verified.

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Section: Injection Machine Parametersmentioning

confidence: 99%

Energy-Efficient Enhancement for Viscoelastic Injection Rheomolding Using Hierarchy Orthogonal Optimization

Wang

Zhang

2018

Mathematical Problems in Engineering

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“…When the jumps are governed by an underlying Markov chain, the system dynamics can then be well described by Markov jump systems and be amenable to thorough theoretical analysis. Various results on Markov jump systems have been reported . It is, therefore, natural to carry out studies related with the stochastic case of positive systems.…”

Section: Introductionmentioning

confidence: 99%

Descriptor state‐bounding observer design for positive Markov jump linear systems with sensor faults: Simultaneous state and faults estimation

Song

Lam

Chen

et al. 2020

Intl J Robust & Nonlinear

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Summary This article presents a descriptor observer design approach for positive Markov jump linear systems subject to interval parameter uncertainties and sensor faults. First, by taking the sensor fault term as an auxiliary state, an augmented descriptor system is constructed. A pair of positive observers with state‐bounding feature is then proposed, which enables simultaneous estimation of the system state and sensor faults. A necessary and sufficient condition on existence of the desired state‐bounding observer is derived by considering positivity and robust mean exponential stability of corresponding observer error dynamics. An iterative optimization algorithm is developed for the computation of the optimized observer matrices. Finally, a numerical example is presented to show the validity of the proposed methods.

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“…In particular, sliding mode control (SMC) has been widely applied to deal with FTC problems as it has strong robustness to against the parameter uncertainties and unknown external disturbances. Some fundamental FTC schemes‐based SMC approaches have been reported …”

Section: Introductionmentioning

confidence: 99%

Asynchronous adaptive output feedback sliding mode control for Takagi‐Sugeno fuzzy Markovian jump systems with actuator faults

Liu

Zhang

et al. 2019

Adaptive Control & Signal

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Summary In this article, the problem of asynchronous adaptive dynamic output feedback sliding mode control (SMC) for a class of Takagi‐Sugeno (T‐S) fuzzy Markovian jump systems (MJSs) with actuator faults is investigated. The asynchronous dynamic output feedback control strategy is employed, as the nonsynchronization phenomenon of jump modes exists between the plant and the controller. A novel asynchronous adaptive SMC approach is proposed to solve the synthesis problem for T‐S fuzzy MJSs with actuator faults. Sufficient conditions for stochastic asymptotic stability of T‐S fuzzy MJSs are given. Under the designed asynchronous adaptive SMC scheme, the effects of actuator faults and external disturbance can be completely compensated and the reachability of sliding surface is ensured. Finally, an example is provided to demonstrate the effectiveness of the proposed design techniques.

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Adaptive Sliding-Mode Control of Markov Jump Nonlinear Systems With Actuator Faults

Cited by 360 publications

References 15 publications

Energy-Efficient Enhancement for Viscoelastic Injection Rheomolding Using Hierarchy Orthogonal Optimization

Energy-Efficient Enhancement for Viscoelastic Injection Rheomolding Using Hierarchy Orthogonal Optimization

Descriptor state‐bounding observer design for positive Markov jump linear systems with sensor faults: Simultaneous state and faults estimation

Asynchronous adaptive output feedback sliding mode control for Takagi‐Sugeno fuzzy Markovian jump systems with actuator faults

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