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model reference control for Linear Time-Varying Systems: A Direct Parametric Approach

IEEE ACCESS 2020年 8卷 61202-61212页

作者： Liu, Yin-Dong Wang, Li-Mei Liu, Long-Wen Shenyang Univ Technol Sch Elect Engn Shenyang 110870 Peoples R China Northeast Elect Power Univ Sch Automat Engn Jilin 132012 Jilin Peoples R China South China Univ Technol Coll Automat Sci & Technol Guangzhou 510641 Peoples R China

This paper investigates model reference control for linear time-varying (LTV) systems. It is shown that the problem can be decomposed into two sub-problems: a state feedback stabilization problem of LTV systems and a feed-forward compensation problem. Firstly, the sufficient condition for the existence of the model reference control is deduced. The condition concerns two coefficient matrices such that two matrix equations are met simultaneously, and the state feedback gain matrix stabilizes LTV systems according to the unified spectral theory. Secondly, generally complete parametrization of the model reference tracking controller including a state feedback controller and a feed-forward compensator is proposed based on the solution to a type of generalized Sylvester matrix equations. Furthermore, a general procedure for solving the model reference control problem is also provided. Finally, a numerical example shows the feasibility and effectiveness of the parametric design approach to the model reference control in LTV systems.

关键词： Linear time-varying systems model reference control parametric approach PD-eigenstructure Sylvester equations

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Retrospective-cost-based model reference adaptive control of nonminimum-phase systems

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INTERNATIONAL JOURNAL OF ADAPTIVE control AND SIGNAL PROCESSING 2024年第7期38卷 2404-2422页

作者： Mohseni, Nima Bernstein, Dennis S. Univ Michigan Dept Aerosp Engn 1320 Beal Ave Ann Arbor MI 48109 USA

This paper presents a novel approach to model reference adaptive control inspired by the adaptive pole-placement controller (APPC) of Elliot and based on retrospective cost optimization. Retrospective cost model reference adaptive control (RC-MRAC) is applicable to nonminimum-phase (NMP) systems assuming that the NMP zeros are known. Under this assumption, the advantage of RC-MRAC is a reduced need for persistency. The present paper compares APPC and RC-MRAC under various levels of persistency in the command for minimum-phase and NMP systems. It is shown numerically that the model-following performance of RC-MRAC is less sensitive to the persistency of the command compared to APPC at the cost of knowledge of the NMP zeros. RC-MRAC is also shown to be applicable for disturbance rejection under unknown harmonic disturbances.

关键词： adaptive control disturbance rejection model free control model reference control nonminimum-phase pole placement

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model reference control for SISO 2-D System with Input Delay

Model Reference Control for SISO 2-D System with Input Delay

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International Mechatronics Conference

作者： Kurek, Jerzy E. Warsaw Univ Sci & Technol Inst Automatyki & Robotyki Ul Boboli 8 PL-02525 Warsaw Poland

The model reference control (MRC) algorithm for SISO 2-D system with input delay is presented. There are given condition for the existence of the controller. The proposed approach is illustrated by numerical example.

ISBN: (纸本)9783030299934;9783030299927

关键词： model reference control 2-D system Input delay system Dead time system

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Robustness Analysis of the model reference control for Active Suspension System

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SAE INTERNATIONAL JOURNAL OF VEHICLE DYNAMICS STABILITY AND NVH 2020年第2期4卷 165-177页

作者： Kaldas, Mina M. Soliman, Aref M. A. Abdallah, Sayed A. Amien, Fomel F. Menia Univ Al Minya Egypt Benha Univ Banha Egypt

This article presents a robustness analysis study for the model reference controller ("MRC") of active suspension system. The MRC employs both suspension look-ahead preview and wheelbase preview concepts. The methodology of the MRC is based on the ideal hybrid skyhook-groundhook scheme. A 13 degree of freedom full vehicle model is developed and validated. The engine mass, driver seat, and anti-roll bar are considered in the model. The MRC strategy uses eight proportional-integral-derivative (PID) controllers for both body and wheel control. A gradient based on optimization algorithm is applied to obtain the controller parameters using a cost function including both ride comfort and road holding performance. The robustness analysis of the controller is performed by evaluating the MRC controller performance under different driving conditions, including different road profiles, different vehicle speeds, and different vehicle loading. Furthermore, the effect of the variable design parameters of the suspension system is also investigated. The results showed that the MRC for active suspension provides robust and significant improvement in both ride comfort and road holding performance of the vehicle under different operating conditions.

关键词： model reference control Active Suspension Robustness Analysis Skyhook Groundhook Hybrid Suspension

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A Frequency Domain Approach to model reference control

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IFAC-PapersOnLine 2021年第7期54卷 216-221页

作者： Berneman Marc Pintelon Rik Lataire John Vrije Universiteit Brussel dept. ELEC Pleinlaan 2 1050 Brussel Belgium

Data-driven model reference control allows for the design of a controller from input and output data when a parametric model of the system is not available. In this work we propose to use advanced nonparametric frequency response function estimation methods to aid in the model reference control task. This allows for a convenient way to extend model reference control to continuous-time systems. Moreover, we also outline a procedure that implements frequency weighing to achieve the Cramér-Rao lower bound in the case that the ideal controller is realizable and in the case that the input is also perturbed by noise. The proposed methods are used to design an analog controller for a continuous-time system.

关键词： Data-driven control Nonparametric Methods Frequency Domain Identification model reference control Frequency Response Function

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Finite-Time H∞ model reference control of SLPV Systems and Its Application to Aero-Engines

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IEEE ACCESS 2019年 7卷 43525-43533页

作者： Huang, Xiaoping Wu, Caiyun Liu, Yiping Northwestern Polytech Univ Sch Comp Sci Xian 710129 Shaanxi Peoples R China Shenyang Ligong Univ Sch Equipment Engn Shenyang 110159 Liaoning Peoples R China Northeastern Univ Sch Informat Sci & Engn Shenyang 110819 Liaoning Peoples R China

In this paper, the finite-time H-infinity model reference tracking control problem for switched linear parameter-varying (SLPV) systems is considered. The associated error SLPV system is obtained by designing the SLPV reference model based on a set of affine Sylvester equations. By using the mode-dependent average dwell time (MDADT) approach, sufficient conditions are deduced to guarantee the finite-time boundedness with a prescribed H-infinity performance of the error SLPV system. The design problem of the model reference SLPV controller is converted into the design of the reference model and the analysis of the finite-time H-infinity performance of the error SLPV system. Consequently, the relationship among the MDADT, the exogenous disturbance and the finite-time intervals is established. Finally, an application regarding the speed tracking control of a turbofan engine is given to verify the effectiveness of the acquired results.

关键词： Switched linear parameter-varying (SLPV) system finite-time H-infinity control model reference control aero-engine control

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Non-Causal controller Approximation Methodology Augmented with model reference control – Robust Design

Non-Causal Controller Approximation Methodology Augmented wi...

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作者： Kopasakis, G National Aeronautics and Space Administration Washington DC. Glenn Research Center Cleveland Ohio United States

This paper describes the development of a new control design methodology based on a non-causal controller structure and its approximation. The non-causal controller design is based on a loop shaping approach. Partial fraction decomposition is used, along with derivative approximations, to derive a proper transfer function design for a causal control structure. The premise for this non-causal control methodology is that the phase delay as a function of frequency ideally remains within approximately -90o, which tends to make the system robustly stable to uncertainties in the plant dynamics. To have a predictable control system response in lieu of the tolerance of this methodology to relatively large uncertainty in the plant dynamics, the approach is augmented with model reference control. The addition of model reference control can potentially further enhance the robustness of the design. A control system design example is presented in this paper, along with simulation results, to demonstrate the high degree of robustness of this non-causal methodology and its augmentation.

关键词： control systems Feedback control model reference control Root locus control design Robust control Loop shaping control design Classical control

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A neuroadaptive architecture for model reference control of uncertain dynamical systems with performance guarantees

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SYSTEMS & control LETTERS 2019年 125卷 37-44页

作者： Arabi, Ehsan Yucelen, Tansel Gruenwald, Benjamin C. Fravolini, Mario Balakrishnan, Sivasubramanya Nguyen, Nhan T. Univ S Florida Dept Mech Engn Tampa FL USA Missouri Univ Sci & Technol Dept Mech & Aerosp Engn Rolla MO USA Perugia Univ Dept Elect & Informat Engn Perugia Italy NASA Ames Res Ctr Moffett Field CA 94035 USA

Neuroadaptive control systems have the capability to approximate unstructured system uncertainties on a given compact set using neural networks. Yet, a challenge in their design is to guarantee the closed-loop system trajectories stay in this set such that the universal function approximation property is satisfied and the overall system stability is achieved. To address this challenge, we present and analyze a new neuroadaptive architecture in this paper for model reference control of uncertain dynamical systems with strict performance guarantees. Specifically, the proposed architecture is predicated on a novel set-theoretic framework and has the capability to keep the closed-loop system trajectories within an a-priori, user-defined compact set without violating the universal function approximation property. A transport aircraft example is also given to complement the presented theoretical results. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Uncertain systems model reference control Neuroadaptive control Stability and performance guarantees

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model reference Tracking control Solutions for a Visual Servo System Based on a Virtual State from Unknown Dynamics

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ENERGIES 2022年第1期15卷 267页

作者： Lala, Timotei Chirla, Darius-Pavel Radac, Mircea-Bogdan Politehn Univ Timisoara Dept Automat & Appl Informat Timisoara 300223 Romania

This paper focuses on validating a model-free Value Iteration Reinforcement Learning (MFVI-RL) control solution on a visual servo tracking system in a comprehensive manner starting from theoretical convergence analysis to detailed hardware and software implementation. Learning is based on a virtual state representation reconstructed from input-output (I/O) system samples under nonlinear observability and unknown dynamics assumptions, while the goal is to ensure linear output reference model (ORM) tracking. Secondary, a competitive model-free Virtual State-Feedback reference Tuning (VSFRT) is learned from the same I/O data using the same virtual state representation, demonstrating the framework's learning capability. A model-based two degrees-of-freedom (2DOF) output feedback controller serving as a comparisons baseline is designed and tuned using an identified system model. With similar complexity and linear controller structure, MFVI-RL is shown to be superior, confirming that the model-based design issue of poor identified system model and control performance degradation can be solved in a direct data-driven style. Apart from establishing a formal connection between output feedback control, state feedback control and also between classical control and artificial intelligence methods, the results also point out several practical trade-offs, such as I/O data exploration quality and control performance leverage with data volume, control goal and controller complexity.

关键词： reinforcement learning and approximate dynamic programming virtual state feedback reference tuning model reference control unknown dynamics input-output observable system visual servo image processing

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Proper closed-loop specifications for data-driven model-reference control 24

Proper closed-loop specifications for data-driven model-refe...

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24th International Symposium on Mathematical Theory of Networks and Systems (MTNS)

作者： Breschi, Valentina Formentin, Simone Politecn Milan Dipartimento Elettron & Informaz I-20133 Milan Italy

In control applications where finding a model of the plant is costly and time consuming, direct data-driven approaches represent a valid alternative for the design of model reference controllers. However, the selection of a proper reference model within a model-free setting is known to be a critical task, as such a model typically plays the role of a hyperparameter. In this work, we extend the existing theory so as to compute both a reference model and the corresponding optimal controller parameters from data to satisfy given behavioral bounds on the desired closed-loop performance. The effectiveness of the proposed approach is illustrated on a benchmark simulation example. Copyright (C) 2021 The Authors.

关键词： Data-driven control model reference control bayesian optimization

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