Robust Control of Positive Fractional‐Order Interconnected Systems with Heterogeneous Delays

Hien, Le Van; Chu, Kinh Trong

doi:10.1002/asjc.1739

Cited by 23 publications

(14 citation statements)

References 42 publications

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“…The non‐fragile design is related to the controller gains uncertainty similar to the robust controller, which solves system parameter uncertainty. Recent papers consider the design of a robust controller but neglect the fragile problem of the controller [19–22]. Methods to check the stability conditions of the system against the uncertainty problem include the Kharitonov and Hermite–Biehler theorems [23,24].…”

Section: Introductionmentioning

confidence: 99%

Optimal design of non‐fragile PID controller

Elsisi

2019

Asian Journal of Control

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This paper solves the controller gains uncertainty problem, which may lead to undesirable responses and an unstable system when implemented. A non‐fragile or resilient controller can overcome this problem. The paper suggests a new method to design a non‐fragile proportional‐integral‐derivative (PID) controller for voltage regulation. This method is carried out by applying a constrained genetic algorithm (GA) as a powerful optimization technique to determine the optimal gains of the PID controller. In addition, new developed conditions from the Routh– Kharitonov theorem are taken into account during the optimization operation to ensure system stability and system response. A new time domain objective function is proposed to establish the optimal permissible limits of controller gains to ensure a constraint of good response. The results of the proposed non‐fragile PID controller are compared with the non‐constrained GA‐based PID controller, artificial bee colony (ABC) algorithm‐based PID controller, and Ziegler Nichols (ZN)‐based PID controller. This achieves better results compared with different methods. The controller gains uncertainties test is applied to ensure the non‐fragility of the proposed controller. Furthermore, the system parameters variation test is applied to check the robustness of the controller based on the suggested method. The designed PID controller by this method is more resilient and less design time is required. The proposed controller and the system are carried out and studied by utilizing MATLAB/Simulink.

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Section: Introductionmentioning

confidence: 99%

Optimal design of non‐fragile PID controller

Elsisi

2019

Asian Journal of Control

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“…Positive reduced-order functional observers for positive fractional order interconnected time-delay systems were designed by [20]. e problem of robust stabilization for positive fractional order interconnected systems with heterogeneous timevarying delays was proposed by [21]. e robust decentralized fault-tolerant resilient control for fractional order large-scale interconnected uncertain system was investigated in [22].…”

Section: Introductionmentioning

confidence: 99%

Robust Stabilization of Nonlinear Fractional Order Interconnected Systems Based on T-S Fuzzy Model

2020

Complexity

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This paper concerns robust stabilization of nonlinear fractional order interconnected systems. Based on uncertain fractional order Takagi–Sugeno fuzzy model and the fractional order extension of lyapunov direct method, a parallel distributed compensate controller is designed to asymptotically stabilize the fractional order interconnected systems. Then, a sufficient condition is given in the format of linear matrix inequalities. Simulation example is given to validate the effectiveness of the approach.

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“…Along with this growing field of research, a number of methods, such as adaptive, backstepping, sliding mode, robust control, etc. [1‐4] has been proposed. Meanwhile, the complexity of the nonholonomic robot system has become greater, and precise mathematical models of the system are very difficult to obtain.…”

Section: Introductionmentioning

confidence: 99%

Adaptive backstepping tracking control of a car with n trailers based on RBF neural network

Jin

Liang

Guo

et al. 2019

Asian Journal of Control

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An adaptive control scheme based on a radial basis function neural network (RBFNN) is proposed for the kinematic model of a car with n trailers. Firstly, a chained system for a kinematic model of a car with n trailers is introduced, then the tracking error system is given. Secondly, a RBFNN controller is designed using the backstepping method and adaptive method, in which neural networks (NNs) are used to approximate the unknown functions in the error system. By using Lyapunov stability theory, the adaptive law of network weights is designed. This method ensures the stability of the error system. Simulation results are provided to verify the effectiveness of the approach.

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Robust Control of Positive Fractional‐Order Interconnected Systems with Heterogeneous Delays

Cited by 23 publications

References 42 publications

Optimal design of non‐fragile PID controller

Optimal design of non‐fragile PID controller

Robust Stabilization of Nonlinear Fractional Order Interconnected Systems Based on T-S Fuzzy Model

Adaptive backstepping tracking control of a car with n trailers based on RBF neural network

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