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predictor-based model reference adaptive control for a vehicle lateral dynamics considering uncertainties

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND control ENGINEERING 2015年第9期229卷 797-807页

作者： Khosravi, Alireza Lachini, Zahra Sarhadi, Pouria Babol Noshirvani Univ Technol Fac Elect & Comp Engn Babol Sar Iran Amol Inst Higher Educ Amol *** Iran Islamic Azad Univ South Tehran Branch Dept Control Engn Tehran Iran

This article deals with the design and analysis of state predictor-based model reference adaptive control for a vehicle lateral dynamics. The goal of this article is to achieve the desired tracking in the presence of uncertainty in order to guarantee the stability as well as improving the performance of the vehicle. Through Lyapunov stability analysis, the adaptive laws of stable predictor-based state feedback have been derived. In order to evaluate the advantages of proposed controller, first the performance of non-adaptive linear quadratic regulator controller in nominal conditions has been presented. By adding uncertainty to the vehicle dynamics, the performance of controller has been reduced. Then, by augmenting model reference adaptive control to linear quadratic regulator, the performance has been improved. Finally, a considerable improvement has been achieved in transient response and control signal using predictor-based model reference adaptive control. Simulation results show that by adding predictor-based model reference adaptive control to the system, uncertain part of the vehicle dynamics is approximated, and the tracking structure of integrated control (linear quadratic regulator+predictor-based model reference adaptive control) has been successful.

关键词： predictor-based model reference adaptive control vehicle lateral dynamic uncertainty linear quadratic regulator controller tracking error

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control of a jet engine using predictor-based adaptive strategy in different flight modes

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND control ENGINEERING 2023年第8期237卷 1349-1364页

作者： Ranjbar, Abedin Khosravi, Alireza Ahmadian, Narjes Babol Noshirvani Univ Technol Dept Elect & Comp Engn Babul Iran

In this article, a predictor-based model reference adaptive control method is proposed for a JetCat SPT5 turboshaft engine in full thrust, cruise, and idle modes. In the predictor-based model reference adaptive control method, in addition to the tracking error, the predictor error is also utilized in adaptive laws to achieve the desired control objectives, such as improving the tracking performance and control signals, and reducing the tracking error. The proposed method is implemented on a turboshaft engine system with actual dynamic values. First, three properly separated equilibrium points are selected on the nominal plant equilibrium manifold to linearize the plant model at the equilibrium points. Then, the predictor-based model reference adaptive control controller is designed and investigated for the three equilibrium points generating three operating modes of the engine, that is, full thrust, cruise, and idle. The stability of the control system is proved by the Lyapunov method. To evaluate the efficiency of the state predictor method in the simulation scenarios, the proposed method is compared with the classic model reference adaptive control method. The simulation results illustrate the superiority of the predictor-based model reference method due to the reduction of unwanted fluctuations in tracking performance, faster convergence of the tracking error to zero, and smoother control signals for all the equilibrium points.

关键词： model reference adaptive control predictor-based model reference adaptive control gas turbine JetCat SPT5 turboshaft engine Lyapunov stability

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