Sage Journals: Discover world-class research

Abstract

Drawing from Lyapunov stability theory, a single input single output model reference adaptive control (MRAC) system using a unified format is researched. A novel design approach is proposed, wherein the control system utilizes the measured value of the model output, thus circumventing issues associated with the unmeasured output differential value of the controlled plant. Because of taking state variables from the model, the system’s resilience against disturbances is notably strengthened. In contrast to the augmentation error signal design method, this approach allows for the derivation of the adaptive control law without the need for an augmentation error signal. Consequently, there is a reduction in the number of adjustable parameters, and the elimination of a set of filters significantly simplifies the system structure, rendering it more amenable to engineering implementation. This streamlined approach promises enhanced efficiency and ease of deployment in practical applications.

Keywords

model reference adaptive control (MRAC)Lyapunov stability theory taking state variables from the modle strictly positive real uniform format

Get full access to this article

View all access options for this article.

References

Sahu

Dey

. Maximum power point tracking using adjustable gain based model reference adaptive control. J Power Electron 2022; 22: 138–150.

Kang

Yang

, et al. Fractional-order robust model reference adaptive control of piezo-actuated active vibration isolation systems using output feedback and multi-objective optimization algorithm. J Vib Control 2020; 26(1-2): 19–35.

Kim

Choi

Jin-Woo

. MRAC-based voltage controller for three-phase CVCF inverters to attenuate parameter uncertainties under critical load conditions. IEEE Trans Power Electron 2020; 35(1): 1002–1013.

Banga-Banga Pierre-Patrick

T-W

Darcy Mfoumboulou

, et al. Power system rotor angle stability enhancement using lyapunov-based trajectory tracking controller and model reference adaptive control. Energies 2022; 15(22): 8479.

Wang

Yang

, et al. A neural network based MRAC scheme with application to an autonomous nonlinear rotorcraft in the presence of input saturation. ISA (Instrum Soc Am) Trans 2021; 115: 1–11.

Kun-Yung

. A new model reference adaptive control with the disturbance observer-based adaptation law for the Nonlinear Servomechanisms: SISO and MIMO Systems. Asian J Control 2021; 23: 2597–2616.

Dixit

Montanaro

Dianati

, et al. Integral MRAC with bounded switching gain for vehicle lateral tracking. IEEE Trans Control Syst Technol 2021; 29(5): 1936–1951.

Fadili

Boumhidi

. Fault tolerant control for wind turbine system based on model reference adaptive control and particle swarm optimization algorithm. J Circ Syst Comput 2020; 29(03): 2050037.

Gai

Jiao

, et al. Application of a new model reference adaptive control based on PID control in CNC machine tool. Machines 2021; 9(11): 274.

10.

Bomfim

Lima

Monteiro

, et al. Novel hybrid (PID + MRAC) adaptive controller for an air levitation system. IEEE Latin America Trans 2021; 19(8): 1400–1409.

11.

Gai

Jiao

, et al. Application of a new model reference adaptive control based on PID control in CNC machine tools. Machines 2021; 9(11): 274.

12.

Bomfim

MHS

Monteiro

Lima

. Modelling, simulation and implementation of a hybrid model reference adaptive controller applied to a manipulator driven by pneumatic artificial muscles. Robotica 2022; 40(6): 1894–1918.

13.

Roshanian

Rahimzadeh

. Novel model reference adaptive control with application to wing rock example. Proc Inst Mech Eng G J Aerosp Eng 2021; 235(13): 1911–1929.

14.

Wang

Zhang

, et al. Study on application of model reference adaptive control in fast steering mirror system. Optik 2018; 172: 995–1002.

15.

Liu

Zhang

Luo

. Model reference adaptive control for aero-engine based on system equilibrium manifold expansion model. Int J Control 2021; 96(4): 884–899.

16.

Manna

Akella

Singh

. A novel MRAC-MPPT scheme to enhance speed and accuracy in PV systems. Iran J Sci Technol Trans Electr Eng 2023; 47(1): 233–254.

17.

Nazari

Babaei

Nazari

. Nonlinear SDRE based adaptive fuzzy control approach for age-specific drug delivery in mixed chemotherapy and immunotherapy. Biomed Sig Proc Contr 2021; 68: 102687.

A new MRAC system design approach based on Lyapunov theory taking state variables from the model

Abstract

Keywords

Get full access to this article

References