A robust model reference adaptive control for non-minimum phase systems with unknown or time-varying delay

Makoudi, M.; Radouane, L.

doi:10.1016/s0005-1098(99)00223-x

Cited by 16 publications

(5 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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

View full text Add to dashboard Cite

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.

show abstract

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

View full text Add to dashboard Cite

show abstract

“…to estimate the parameters of the systems. In discrete time, different robust adaptive control schemes have been developed and applied to the class of linear systems described by a mathematical model ARX in the presence of unmodelled dynamics [30][31][32]. Different robust adaptive control of monovariable systems have been developed on the basis of the modified recursive least squares algorithm M-RLS with approach robustness dead zone [33][34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Self-Tuning Control Scheme Based on the Robustnessσ-Modification Approach

Touijer

Kamoun

Essounbouli

et al. 2017

Journal of Electrical and Computer Engineering

View full text Add to dashboard Cite

This paper deals with the self-tuning control problem of linear systems described by autoregressive exogenous (ARX) mathematical models in the presence of unmodelled dynamics. An explicit scheme of control is described, which we use a recursive algorithm on the basis of the robustnessσ-modification approach to estimate the parameters of the system, to solve the problem of regulation tracking of the system. This approach was designed with the assumptions that the norm of the vector of the parameters is well-known. A new quadratic criterion is proposed to develop a modified recursive least squares (M-RLS) algorithm withσ-modification. The stability condition of the proposed estimation scheme is proved using the concepts of the small gain theorem. The effectiveness and reliability of the proposed M-RLS algorithm are shown by an illustrative simulation example. The effectiveness of the described explicit self-tuning control scheme is demonstrated by simulation results of the cruise control system for a vehicle.

show abstract

“…In practice, most control plants are multivariable and are characterized by widely changing environmental disturbances and various work conditions. Thus, it is important to investigate effective robust adaptive control techniques for uncertain MIMO nonlinear systems [1][2][3][4][5][6][7]. Robust adaptive control based on universal function approximators (such as fuzzy systems and neural networks) has been extensively studied [8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy tracking control for a class of uncertain MIMO nonlinear systems using disturbance observer

Chen

2012

Sci. China Inf. Sci.

View full text Add to dashboard Cite

Citation: CHEN, M., CHEN, W-H. and WU, Q-X., 2014. Adaptive fuzzy tracking control for a class of uncertain MIMO nonlinear systems using disturbance observer. Science China Information Sciences, 57 (1), pp 1-13.Additional Information:• Loughborough, Leicestershire LE11 3TU, UK Abstract: In this paper, adaptive fuzzy tracking control is proposed for a class of multi-input and multi-output (MIMO) nonlinear systems in the presence of system uncertainties, unknown nonsymmetric input saturation and unknown external disturbances. For the MIMO nonlinear system, the time-varying external disturbance cannot be directly measured which is estimated via disturbance observer. By choosing the appropriate gain matrix, disturbance observer can approximate the unknown disturbance well and the estimate error converges to a compact set. And then, fuzzy logic systems (FLS) are used to approximate the system uncertainty of MIMO nonlinear systems.Based on outputs of disturbance observer and FLS, adaptive tracking control is presented for the uncertain MIMO nonlinear system. Considering the unknown non-symmetric input saturation and control singularity case, adaptive fuzzy tracking control is developed via disturbance observer and FLS approximation technique. The effects of unknown input saturation and control singularity are treated as a part of system compound disturbance which is estimated using disturbance observer.Under the proposed tracking control techniques, semi-global uniform boundedness of the closed-loop signals is guaranteed via Lyapunov analysis. Numerical simulation results are presented to illustrate the effectiveness of the proposed tracking control schemes.

show abstract

A robust model reference adaptive control for non-minimum phase systems with unknown or time-varying delay

Cited by 16 publications

References 16 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

Self-Tuning Control Scheme Based on the Robustnessσ-Modification Approach

Adaptive fuzzy tracking control for a class of uncertain MIMO nonlinear systems using disturbance observer

Contact Info

Product

Resources

About