A gradient descent control for output tracking of a class of non-minimum phase nonlinear systems

Jouili, Khalil; Braïek, Naceur Benhadj

doi:10.1016/j.jart.2016.09.006

Cited by 7 publications

(2 citation statements)

References 25 publications

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“…Non-minimum phase systems refer to systems with one or more zeros, poles, or delays on the right half plane, which plays a crucial role in the analysis and control design of industrial control, power systems, and so on. 21,22 The transfer function for a typical non-minimum phase system is defined as Equation (36).…”

Section: Non-minimum Phase Systemmentioning

confidence: 99%

Truncation error correction by designing input-adjustment-output coefficients for dynamic matrix control based on cubic spline function

Chen,

Cao,

Qing

et al. 2023

SIMULATION

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The truncation error is an important problem in the dynamic matrix control (DMC) algorithm. Generally, the dynamic information of a plant for the traditional DMC algorithm is determined by the step response. However, the step response of the plant is limited in practice, which leads to the truncation error of the modeling horizon in the feedback correction of DMC algorithm. A truncation error correction method based on cubic spline function is proposed for DMC algorithm, which is realized by designing coefficients and tracking the dynamic response of the system. In the feedback correction of DMC algorithm, the relationship between the correction parameter and the correction difference is constructed by the fitting of cubic spline functions on the intervals. A truncation error correction procedure is presented to calculate the correction parameters by inputting of the correction difference into the relationship. Then, the control increment and predicted model output are computed based on the correction parameters and updated shift matrix. Finally, numerical experiments demonstrate that the control performance of the proposed DMC algorithm has been much improved compared to that of traditional DMC algorithm.

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Section: Non-minimum Phase Systemmentioning

confidence: 99%

Truncation error correction by designing input-adjustment-output coefficients for dynamic matrix control based on cubic spline function

Chen,

Cao,

Qing

et al. 2023

SIMULATION

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“…Then, the angular position of the pole is controlled using input-output feedback linearization technique so that it can track the reference angular position. Now, if the position of the cart converges to zero, the angular position of the pole will converge to zero, too (Henmi et al, 2010, July;Jouili & Braiek, 2016). If the control effort u for Eq.…”

Section: Input-output Feedback Linearizationmentioning

confidence: 99%

Parametric uncertainty handling of under-actuated nonlinear systems using an online optimal input–output feedback linearization controller

Mahmoodabadi

Sahnehsaraei

2021

Systems Science & Control Engineering

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This research introduces a new online optimal control based on the input-output feedback linearization and a multi-crossover genetic algorithm for under-actuated nonlinear systems having parametric uncertainties. At first, the input-output feedback linearization method is successfully implemented to derive the control law for a two degrees of freedom cart-pole nonlinear system. Then, the regarded optimization algorithm is applied to find the design parameters of the controller for different values of the uncertain variables. Next, an approximation function is suggested to calculate the optimum gains of the controller in the presence of the uncertainties in the system parameters. The simulation results are illustrated to prove the effectiveness and adeptness of the introduced scenario to overcome some common issues in the actual systems, i.e. under-actuating nonlinearities and uncertainties.

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RLCP-Compatible Virtual Laboratories with 3D-Models and Demonstration Mode: Development and Application in e-Learning

Lisitsyna

Efimchik

Izgareva

2017

Smart Education and E-Learning 2017

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A gradient descent control for output tracking of a class of non-minimum phase nonlinear systems

Cited by 7 publications

References 25 publications

Truncation error correction by designing input-adjustment-output coefficients for dynamic matrix control based on cubic spline function

Truncation error correction by designing input-adjustment-output coefficients for dynamic matrix control based on cubic spline function

Parametric uncertainty handling of under-actuated nonlinear systems using an online optimal input–output feedback linearization controller

RLCP-Compatible Virtual Laboratories with 3D-Models and Demonstration Mode: Development and Application in e-Learning

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