Design of a Nonlinear Predictive Controller for a Fractional-Order Hydraulic Turbine Governing System with Mechanical Time Delay

Tian, Yuqiang; Wang, Bin; Chen, Diyi; Wang, Shaokun; Chen, Peng; Yang, Ying

doi:10.3390/en12244727

Cited by 5 publications

(2 citation statements)

References 46 publications

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“…Among the three fractional calculus ideas discussed, it is noteworthy that both the R-L and C types are derived from the G-L type. 19 Upon closer examination of definitions ( 4) and ( 8), it becomes apparent that the R-L type definition can be conceived as a derivative of function f(t) with a positive a-order that is not an integer. This derivative is obtained by initially subjecting the function to an integration of order m2a, followed by a differentiation of order m. The C type definition can be seen as an a-order derivative of the function f(t), with an initial m-order differentiation followed by m2a order integration.…”

Section: Fractional Calculus Theorymentioning

confidence: 99%

Design and performance evaluation of a novel fractional order PID control strategy for vehicle semi-active suspension

Li,

Xu,

Ruan

et al. 2024

Advances in Mechanical Engineering

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The performance of a semi-active suspension depends on the quality of the control algorithm. Considering the limitations of conventional PID controllers within intricate nonlinear systems, such as imprecise parameter tuning and performance deterioration, we introduced a fractional-order PID (FOPID) control strategy for vehicle semi-active suspension, this approach amalgamates fractional-order theory with conventional PID control to enhance both the controllable scope and precision of the suspension system. Research on semi-active suspension control was conducted using a nonlinear dynamic model of a quarter vehicle. Simulations and analyses were performed utilizing random road excitation and impact road excitation as input signals for both FOPID control, Fuzzy-PID control, and conventional PID control strategies. The analysis findings demonstrated that in the presence of random road excitation, the semi-active suspension system controlled by FOPID reduced vehicle body acceleration by 18.9%, in contrast to a 14.7% reduction by the Fuzzy-PID-controlled suspension, and a 12% reduction achieved by the PID-controlled suspension when compared to the passive suspension. In response to impact road excitation, the suspension system under FOPID control effectively mitigated the peak value of vehicle body acceleration by 29.4%, surpassing the 25.2% reduction achieved by Fuzzy-PID-controlled suspension, and the 24.6% reduction achieved by the PID-controlled suspension. The simulation outcomes substantiated that ride comfort and handling stability of the semi-active suspension system were effectively improved by the implementation of FOPID control.

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Section: Fractional Calculus Theorymentioning

confidence: 99%

Design and performance evaluation of a novel fractional order PID control strategy for vehicle semi-active suspension

Li,

Xu,

Ruan

et al. 2024

Advances in Mechanical Engineering

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“…Similarly, in [18], the authors proposed algorithm for a robust adaptive fuzzy neural network control and created a PID controller for the heading control of UMV (Unmanned Marine Vehicles). Many other nonlinear control models have been proposed and evaluated to establish mathematical models from different perspectives [19][20][21][22]. However, in terms of energy-saving performance, additional research is required.…”

Section: Introductionmentioning

confidence: 99%

Using Sine Function-Based Nonlinear Feedback to Control Water Tank Level

et al. 2021

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This manuscript addresses the feasibility and significance of using a sine function to modify the system error of a normal linear feedback control to achieve more efficient capabilities in terms of energy-saving. The associated mathematic modeling and assessment were demonstrated by presenting a case analysis on the capabilities of controlling water level for a single tank. The principle of robust control and the theories and detailed algorithm of Lyapunov stability were applied to assess the result derived by novel nonlinear feedback in the form of sine function for optimizing the robustness of the PID (Proportional–Integral–Derivative) controller and economizing energy. Two control simulations are compared: nonlinear feedback control using a sine function and conventional fuzzy control. The results reveal that using the nonlinear feedback controller, a reduction of up to 32.9% of the average controlled quantity is achieved, and the performance index is improved by 24.0% with satisfactory robustness. The proposed nonlinear feedback control using a sine function provides simplicity, convenient implementation, and energy efficiency.

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Intelligent robust control for nonlinear complex hydro-turbine regulation system based on a novel state space equation and dynamic feedback linearization

Chen,

Zeng,

Zou

et al. 2024

Energy

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Design of a Nonlinear Predictive Controller for a Fractional-Order Hydraulic Turbine Governing System with Mechanical Time Delay

Cited by 5 publications

References 46 publications

Design and performance evaluation of a novel fractional order PID control strategy for vehicle semi-active suspension

Design and performance evaluation of a novel fractional order PID control strategy for vehicle semi-active suspension

Using Sine Function-Based Nonlinear Feedback to Control Water Tank Level

Intelligent robust control for nonlinear complex hydro-turbine regulation system based on a novel state space equation and dynamic feedback linearization

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