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Circuit realization, chaos synchronization and estimation of parameters of a hyperchaotic system with unknown parameters

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Journal of the Egyptian Mathematical Society 2014年第3期22卷 550-557页

作者： A. Elsonbaty A. Elsaid H.M. Nour Mathematics & Engineering Physics Department Faculty of Engineering Mansoura University PO 35516 Mansoura Egypt

In this article, the adaptive chaos synchronization technique is implemented by an electronic circuit and applied to the hyperchaotic system proposed by Chen et al. We consider the more realistic and practical case where all the parameters of the master system are unknowns. We propose and implement an electronic circuit that performs the estimation of the unknown parameters and the updating of the parameters of the slave system automatically, and hence it achieves the synchronization. To the best of our knowledge, this is the first attempt to implement a circuit that estimates the values of the unknown parameters of chaotic system and achieves synchronization. The proposed circuit has a variety of suitable real applications related to chaos encryption and cryptography. The outputs of the implemented circuits and numerical simulation results are shown to view the performance of the synchronized system and the proposed circuit.

关键词： 34H10 34C28 37M05 Hyperchaos Adaptive synchronization Circuit implementation unknown system parameters

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Decentralised adaptive control design for single-phase parallel-inverter systems

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IET RENEWABLE POWER GENERATION 2019年第15期13卷 2752-2761页

作者： Fan, Bo Guo, Shilin Yang, Qinmin Liu, Wenxin Zhejiang Univ Coll Control Sci & Engn State Key Lab Ind Control Technol Hangzhou 310027 Zhejiang Peoples R China Lehigh Univ Dept Elect & Comp Engn Smart Microgrid & Renewable Technol SMRT Res Lab Bethlehem PA 18015 USA

Single-phase inverters are widely installed to integrate distributed generations into microgrids. To further improve the reliability and flexibility, several inverter modules connected in parallel are usually preferred. Besides achieving bus voltage regulation, another control objective of parallel-inverter systems is to guarantee load current sharing performance among multiple inverter modules. To attain these objectives in the presence of physical differences and uncertain system parameters, advanced control schemes are needed. In this study, a state-feedback decentralised adaptive control algorithm is firstly presented for single-phase parallel-inverter systems with unknown system parameters. Adaptive laws are designed to compensate for the uncertainties. In addition, the proposed control algorithm is decentralised in the sense that only local information is required for each inverter's controller. To overcome the practical problem that not all system states are available due to the presence of the unknown system parameters and load current, an output-feedback version of the decentralised adaptive controller is introduced through observers. The closed-loop system stability is proved via Lyapunov analysis. Finally, extensive simulation studies on parallel-inverter systems of different levels of detail are conducted to illustrate that the proposed control algorithm can provide satisfactory voltage regulation and current sharing performance under various loading conditions.

关键词： invertors stability Lyapunov methods uncertain systems voltage control closed loop systems adaptive control distributed power generation decentralised control control system synthesis power generation control state feedback unknown system parameters system states Lyapunov analysis observers voltage regulation state-feedback decentralised adaptive control algorithm advanced control schemes uncertain system parameters multiple inverter modules load current sharing performance single-phase inverters single-phase parallel-inverter systems decentralised adaptive control design closed-loop system stability decentralised adaptive controller

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Adaptive Control Design for Uncertain Underactuated Cranes With Nonsmooth Input Nonlinearities

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IEEE TRANSACTIONS ON systemS MAN CYBERNETICS-systemS 2023年第2期53卷 1074-1083页

作者： Yang, Yue Ye, Xin Wen, Baoyu Huang, Jiangshuai Su, Xiaojie Chongqing Univ Sch Automat Chongqing 400044 Peoples R China Chongqing Univ Technol Vehicle Engn Inst Chongqing 400054 Peoples R China

This article investigates the control of underactuated crane systems with unknown system parameters and nonsmooth input nonlinearities. To solve this problem, a novel filter-based adaptive control method is designed for the underactuated crane systems. First, since the backstepping control scheme cannot be directly applied to the crane systems, a group of filters is designed such that the crane systems become a class of strict-feedback nonlinear systems in each step of backstepping. Then, in order to ensure that the swing angle and position error converge to the origin, the variable transformation method is adopted. The result demonstrates that the tracking errors of the underactuated crane systems could be guaranteed to converge to a ball of origin with an arbitrarily small radius. Finally, the simulation results show that the proposed scheme is effective.

关键词： Cranes Hysteresis Actuators Control systems Backstepping Adaptive control Mathematical models Adaptive control nonsmooth input nonlinearities underactuated crane unknown system parameters

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Ride comfort improvement using robust multi-input multi-output fuzzy logic dynamic compensator

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF systemS AND CONTROL ENGINEERING 2023年第1期237卷 72-85页

作者： Ozbek, Cengiz Ozguney, Omur Can Burkan, Recep Yagiz, Nurkan Beykent Univ Dept Mech Engn Istanbul Turkey Istanbul Univ Cerrahpasa Dept Mech Engn Istanbul Turkey

This article aims to improve the ride comfort of a vehicle keeping a satisfactory without road-holding performance by a novel adaptive control method that is insensitive to unknown system dynamics, model parameter changes, external disturbances and without any loss in suspension working space. With this purpose in mind, a new fuzzy integrated model-based adaptive control law for vehicle suspension systems is proposed in this study to improve the ride comfort and to ensure the robustness of system towards unknown model parameters and external disturbances. First, a model-based adaptive control law, which has the robust characteristics is presented. Afterwards, a multi-input multi-output fuzzy logic controller is designed to determine the controller gains dynamically. The stability of controller is ensured by Lyapunov Theory to achieve uniform boundedness error convergence. A 4 degree-of-freedom half-car model with active suspension system is used in this study to assess the performance of the controller. The results are compared among passive, model-based adaptive control law-controlled and novel fuzzy model-based adaptive control law-controlled systems. It has been concluded that fuzzy model-based adaptive control law further attenuates linear and angular motions of the vehicle increasing the ride comfort. The robustness is also verified for vehicle components having different possible parameter values. It is noteworthy that suspension working length returns to its initial position. Thus, the vehicle ride comfort is improved with no suspension working space loss. Finally, the economic feasibility of controllers has been checked in terms of energy consumption.

关键词： Ride comfort multi-input multi-output fuzzy logic dynamic compensator unknown system parameters half-car model

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LOWER BOUNDS FOR THE STABILITY MARGIN OF LINEAR CONTINUOUS systemS BASED ON WEIGHTED PERFORMANCE CRITERIA

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IEE PROCEEDINGS-D CONTROL THEORY AND APPLICATIONS 1989年第2期136卷 63-67页

作者： AGATHOKLIS, P SREERAM, V Department of Electrical & Computer Engineering University of Victoria Victoria Canada

In the paper, lower bounds for the stability margin of linear continuous systems with unknown system parameters are developed. These lower bounds are obtained as a function of the weighted performance criteria computed from the measurements of the system's impulse response. The properties of the proposed method are discussed and it is shown that the bounds can be improved by increasing the order of the weighting factor. The method is illustrated by a numerical example.

关键词： linear systems continuous systems stability margin lower bounds weighted performance criteria unknown system parameters impulse response stability criteria Stability in control theory

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PARAMETER-ESTIMATION OF CONTINUOUS LINEAR-systemS USING FUNCTIONAL APPROXIMATION

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COMPUTERS & ELECTRICAL ENGINEERING 1995年第3期21卷 183-187页

作者： MAN, ZH Department of Computer and Communication Engineering Edith Cowan University W.A. 6027 Australia

A novel method to estimate unknown system parameters for SISO linear time invariant systems using functional approximation is proposed. It is shown that the differential equation of a linear time invariant system can be approximated by a finite Taylor series and the unknown system parameters are then estimated by using the information from the Laplace transforms of the input and the output.

关键词： PARAMETER ESTIMATION FUNCTIONAL APPROXIMATION LINEAR system LAPLACE TRANSFORM TAYLOR SERIES HILBERT MATRIX LEAST SQUARES ESTIMATION DIFFERENTIAL EQUATION unknown system parameters POLYNOMIAL SERIES

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Dual Adaptive Extremum Control of a Hammerstein system 22

Dual Adaptive Extremum Control of a Hammerstein System

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22nd Mediterranean Conference on Control and Automation (MED)

作者： Fabri, Simon G. Wittenmark, Bjorn Bugeja, Marvin K. Univ Malta Dept Syst & Control Engn MSD-2080 Msida Malta Lund Univ Dept Automat Control S-22100 Lund Sweden

ISBN: (纸本)9781479959013

This paper proposes a dual adaptive control methodology for extremum control of stochastic Hammerstein systems that are subject to uncertainty and characterised by a nonlinear second-order polynomial function. The design is based on an explicit-type innovations dual cost function that leads to a control law which balances out the need for caution when using uncertain parameter estimates to effect control actions, with the conflicting need to probe the system input so as to reduce parameter uncertainty. This extremum control problem is more challenging than conventional adaptive systems because the reference input is itself a non-linear function of the unknown system parameters. The controller's performance is analysed through extensive Monte Carlo simulations and shown to be superior to other types of adaptive control systems that use a certainty equivalence assumption.

关键词： adaptive control control system synthesis nonlinear functions optimal control parameter estimation stochastic systems uncertain systems control law dual adaptive extremum control system explicit-type innovation dual cost function extensive Monte Carlo simulations nonlinear function nonlinear second-order polynomial function parameter uncertainty reduction stochastic Hammerstein systems uncertain parameter estimates unknown system parameters Adaptive control Cost function Estimation Steady-state Technological innovation Uncertain systems

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Square-Root Adaptive Wave Filtering for Marine Vessels

Square-Root Adaptive Wave Filtering for Marine Vessels

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European Control Conference (ECC)

作者： Kulikova, Maria V. Univ Lisbon Inst Super Tecn CEMAT Av Rovisco Pais 1 P-1049001 Lisbon Portugal

ISBN: (纸本)9783952426937

In this paper, the problem of designing numerically stable recursive estimators for adaptive Wave Filtering (WF) of marine vessels is addressed. The WF technique consists of a recursive optimization procedure to identify the dominant wave frequency (the uncertain parameter) by minimizing an appropriate defined performance index and the application of the Kalman filter for dynamic positioning purpose. The computational approach yields to a set of the filter sensitivity equations and a set of matrix Riccati-type sensitivity equations. Recently proposed WF methodology [1] is based on the conventional Kalman filter and its derivatives (with respect to unknown system parameters) that is known to be numerically unstable. To improve the numerical stability we are focusing in the techniques developed in the Kalman filtering community to solve ill conditioned problems. More precisely, here the square-root variant of the adaptive WF scheme is designed to improve accuracy and robustness for a finite-precision computer arithmetics. Then, it is examined on the dynamic positioning model of marine vessels.

关键词： Kalman filters Riccati equations adaptive filters marine vehicles matrix algebra minimisation numerical stability performance index position control recursive estimation Kalman filter WF technique accuracy improvement computational approach dominant wave frequency identification dynamic positioning filter sensitivity equations finite-precision computer arithmetics ill conditioned problems marine vessels matrix Riccati-type sensitivity equations numerical unstability numerically stable recursive estimator design recursive optimization procedure robustness improvement square-root adaptive wave filtering uncertain parameter unknown system parameters Adaptation models Adaptive systems Filtering Mathematical model Optimization Performance analysis Sensitivity

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Robust adaptive finite-time attitude tracking with an unknown inertia matrix and disturbance 18

Robust adaptive finite-time attitude tracking with an unknow...

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IEEE 18th International Conference on Control and Automation (ICCA)

作者： Garanayak, Chinmay Indian Inst Technol Dept Elect Engn Mumbai 400076 Maharashtra India

ISBN: (纸本)9798350354416;9798350354409

This paper proposes a novel finite-time attitude-tracking controller when the system dynamics are affected by unknown constant disturbances. Also, the inertia matrix and the disturbances affecting the dynamics are unknown. Finite-time attitude tracking for uncertain spacecraft systems is an interesting problem. Due to the inherent non-linear nature of the problem, it becomes challenging to design finite-time attitude-tracking controllers. Hence, we have designed an adaptive control-based finite-time attitude-tracking controller. First, a fixed-time sliding surface was proposed, and hence, after reaching the sliding surface, the attitude tracking error goes to zero in fixed-time. Then, the control torque, which contains adaptive parameter updates for the unknown system inertia matrix, is designed. The control torque ensures that the attitude tracking error reaches the sliding surface in finite time despite the unknown inertia matrix and unknown constant disturbances present in the dynamics so that finite-time attitude tracking can be achieved. Simulations are presented to validate the theoretical results.

关键词： Robust tracking attitude tracking unknown system parameters

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Nonlinear adaptive sliding mode control with application to quadcopters

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NONLINEAR ENGINEERING - MODELING AND APPLICATION 2023年第1期12卷

作者： Mathewson, Ryan Fahimi, Farbod Univ Alabama Huntsville Mech & Aerosp Engn Dept Huntsville AL 35899 USA

Nonlinear adaptive sliding mode control (NASMC) has the capability to adequately control a system whose parameters are unknown to the controller designer. Conventional model-based controllers require a mathematical dynamic model of the system with known parameters. These system parameters are normally determined by extensive system identification experiments, which are expensive and time-consuming to perform. A NASMC approach that does not require known system parameters is proposed. Using NASMC, a controller designer can skip the expensive and time-consuming system parameter identification and fast-forward to the control implementation. In addition, once a controller is derived for a quadcopter using NASMC, the same controller will work on any quadcopter with the same equations of motion but different dynamic parameters. The formulation of the NASMC is presented for general second-order and fourth-order systems. Then, as an implementation example, the application of the general NASMC approach is demonstrated by applying it to a quadcopter unmanned aerial vehicle in simulation.

关键词： nonlinear control nth-order adaptive variable structure control fourth-order quadcopter model single-loop quadcopter control unknown system parameters

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