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Fault-tolerant control of non-linear systems based on adaptive virtual actuator

IET CONTROL THEORY AND APPLICATIONS 2017年第9期11卷 1371-1379页

作者： Yadegar, Meysam Afshar, Ahamad Meskin, Nader Amirkabir Univ Technol Dept Elect Engn Tehran Iran Qatar Univ Dept Elect Engn Doha Qatar

A new adaptive fault-tolerant control architecture for Lipschitz non-linear systems is developed. Specifically, the proposed approach involves a novel adaptive virtual actuator which is inserted between the faulty plant and the nominal controller to hide faults and disturbances from the nominal controller. The envisaged adaptive virtual actuator does not require any information about the nominal controller nor does it require a separate fault detection, isolation and identification unit. Moreover, it can tackle loss of effectiveness and time-varying additive actuator faults as well as an external disturbance, and in addition to the stability of the closed-loop system, it also guarantees that the difference between the states of the nominal and the faulty systems tend to zero. Simulation results corresponding to the lateral directional dynamics of an aircraft demonstrate and illustrate the effectiveness of the proposed adaptive virtual actuator.

关键词： nonlinear control systems adaptive control fault tolerant control time-varying systems closed loop systems stability actuators closed-loop system stability time-varying additive actuator fault adaptive virtual actuator Lipschitz nonlinear system adaptive fault-tolerant control architecture

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Fault-tolerant control for descriptor stochastic systems with extended sliding mode observer approach

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IET CONTROL THEORY AND APPLICATIONS 2017年第8期11卷 1079-1087页

作者： Yu, Jinyong Sun, Yiyong Lin, Weiyang Li, Zhan Harbin Inst Technol Res Inst Intelligent Control & Syst Harbin 150001 Peoples R China Tech Univ Munich Chair Automat Control Engn Theresienstr 90 D-80333 Munich Germany

This study concentrates on the fault-tolerant control and fault estimation problems for a class of descriptor stochastic systems with state-dependent faults. A new extended observer method is presented to solve these design problems. First, the descriptor stochastic system is transformed into a non-singular system, and an augmented system is constructed by assembling the fault states into the augmented vector. Then, a novel sliding mode observer with two discontinuous input terms is designed to estimate the states and faults of system. A state-feedback control scheme based on the state estimates is synthesised to guarantee the closed-loop systems stable. Finally, a numerical example is presented to show the effectiveness of the proposed design approach.

关键词： fault tolerant control stochastic systems variable structure systems observers state feedback control system synthesis closed loop systems stability fault-tolerant control descriptor stochastic systems extended sliding mode observer approach fault estimation problems state-dependent faults nonsingular system augmented system augmented vector discontinuous input terms state-feedback control scheme state estimates closed-loop system stability

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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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Feedback preparation of maximally entangled states of two-qubit systems

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IET CONTROL THEORY AND APPLICATIONS 2016年第3期10卷 339-345页

作者： Zhou, Juan Kuang, Sen Univ Sci & Technol China Dept Automat Hefei Anhui Peoples R China

Bell states play a central role in the field of quantum information. For two-qubit systems, this study proposes a new non-smooth control strategy within the theoretical framework of quantum continuous measurement, and achieves global feedback stabilisation in any target Bell state. For a target Bell state, the authors select one measured observable and two control channels, where the control law associated with one channel is kept constant. They design a non-smooth control law for the other control channel, and prove the stability of the whole closed-loop system. Some simulation experiments show that the control strategy in this paper has a good control effect.

关键词： feedback discrete time systems control system synthesis stability continuous time systems observability closed loop systems closed-loop system stability nonsmooth control law design control channel measured observable channel target Bell state global feedback stabilisation quantum continuous measurement nonsmooth control strategy quantum information two-qubit systems maximally entangled states feedback analysis

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Two-step MPC for systems with input non-linearity and norm-bounded disturbance

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IET CONTROL THEORY AND APPLICATIONS 2019年第2期13卷 183-190页

作者： Wang, Jun Ding, Baocang Wang, Yong Xi An Jiao Tong Univ Sch Elect & Informat Engn Dept Automat Xian 710049 Shaanxi Peoples R China

In this study, a novel two-step model predictive control (MPC) for Hammerstein systems subject to norm-bounded disturbance is addressed. In the first step, the intermediate control law for the linear part of the system is posed as the solution to the unconstrained MPC problem that minimises a quadratic cost function over a given finite time, for which the solution is determined by a novel Riccati iterative equation. In the second step, the actual control move is obtained by solving non-linear algebraic equation group and desaturation. The quadratic boundedness technique is used to specify the stability for closed-loop system with norm-bounded disturbance, and the sufficient conditions for quadratic convergent of the system state are presented. Simulation results demonstrate the effectiveness of the proposed approach to this class of systems.

关键词： predictive control linear algebra stability nonlinear control systems iterative methods closed loop systems Riccati equations control nonlinearities linear systems input nonlinearity norm-bounded disturbance two-step model predictive control linear part unconstrained MPC problem desaturation Hammerstein systems two-step MPC Riccati iterative equation nonlinear algebraic equation quadratic boundedness technique stability intermediate control law closed-loop system stability quadratic convergence quadratic cost function minimisation sufficient conditions

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Backstepping control of sandwich-like non-linear systems with deadzone non-linearity

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IET CONTROL THEORY AND APPLICATIONS 2017年第17期11卷 3122-3129页

作者： Song, Jiawei Zuo, Zongyu Ding, Zhengtao Beihang Univ BUAA Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China Univ Manchester Sch Elect & Elect Engn Manchester M13 9PL Lancs England

This study studies the output tracking control of a class of sandwich-like systems with state-dependent deadzone non-linearity between two cascaded subsystems (e.g. the gear transmission systems). An exact differentiator-based backstepping control for such a sandwich-like non-linear system is proposed. The proposed controller utilises the high-order sliding mode robust exact differentiator to compensate the impact of non-strict feedback coupling term due to the sandwiched deadzone. The stability of the closed-loop system is guaranteed to be uniform-ultimately bounded and the output tracking error converges to a residual set. Finally, two simulation examples are provided to demonstrate the tracking performance and effectiveness of the proposed controller.

关键词： nonlinear control systems control nonlinearities closed loop systems feedback variable structure systems sandwich-like nonlinear system exact differentiator-based backstepping control high-order sliding mode robust exact differentiator closed-loop system stability

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Adaptive integral sliding mode control with bounded L₂ gain performance of uncertain quantised control systems

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IET CONTROL THEORY AND APPLICATIONS 2015年第15期9卷 2273-2282页

作者： Zheng, Bo-Chao Park, Ju H. Nanjing Univ Informat Sci & Technol Sch Informat & Control CICAEET Nanjing 210044 Jiangsu Peoples R China Yeungnam Univ Dept Elect Engn Kyongsan 712749 South Korea

Adaptive integral sliding mode control (ISMC) is investigated for a class of non-linear uncertain systems considering the mismatch relation between quantisation sensitivity parameters. First, by analysing the operation principle of the encoder/decoder, a mismatched relation between the quantisation parameters is established by using a time-varying ratio model, where the boundaries of the time-varying ratio can be unknown, regarding the existing cases as special ones. Second, using linear matrix inequality techniques, the prescribed bounded L-2 gain performance condition is obtained for the sliding dynamics. Sequently, based on the formed boundary unknown time-varying ratio relation, adaptive ISMC laws are designed to ensure the reachability of the sliding manifold, then the establishment of the stability of the closed-loop system. Finally, an example is provided to illustrate the effectiveness of the proposed methods.

关键词： adaptive control variable structure systems uncertain systems nonlinear control systems time-varying systems linear matrix inequalities closed loop systems stability reachability analysis control system synthesis adaptive integral sliding mode control bounded L-2 gain performance uncertain quantised control systems nonlinear uncertain systems quantisation sensitivity parameters encoder operation principle decoder operation principle mismatched relation sliding dynamics boundary unknown time-varying ratio relation adaptive ISMC law design sliding manifold reachability closed-loop system stability

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Dynamic surface control for a class of stochastic non-linear systems with input saturation

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IET CONTROL THEORY AND APPLICATIONS 2016年第1期10卷 35-43页

作者： Yan, Xiaohui Chen, Mou Wu, Qingxian Shao, Shuyi Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing Jiangsu Peoples R China Hefei Univ Dept Math & Phys Hefei Peoples R China Nanjing Univ Aeronaut & Astronaut Jiangsu Key Lab Internet Things & Control Technol Nanjing Jiangsu Peoples R China

In this study, the problem of adaptive dynamic surface control (DSC) design is investigated for a class of stochastic non-linear systems with input saturation. The saturation non-linearity is modelled via the existing dead zone-based model of saturation. Furthermore, the packaged unknown functions are tackled using the neural networks. On the basis of the DSC technique, an adaptive controller is designed for stochastic non-linear systems with input saturation. The proposed control scheme can guarantee the closed-loop system stability, which shows that all closed-loop system signals are semi-globally uniformly ultimately bounded in the sense of probability and the tracking error converges to a small neighbourhood of the origin. Simulation results are provided to demonstrate the effectiveness and performance of the proposed approach.

关键词： stochastic systems nonlinear control systems adaptive control control system synthesis control nonlinearities neurocontrollers closed loop systems stability stochastic nonlinear systems input saturation adaptive dynamic surface control design DSC saturation nonlinearity dead zone-based model packaged unknown functions neural networks adaptive controller closed-loop system stability

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Neuro-observer based online finite-horizon optimal control for uncertain non-linear continuous-time systems

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IET CONTROL THEORY AND APPLICATIONS 2017年第3期11卷 401-410页

作者： Huang, Yuzhu Beijing Huatsing Gas Turbine & IGCC Technol Co Lt Syst Control Res Sect Tsinghua Sci Pk Beijing 100084 Peoples R China

In this study, within framework of adaptive dynamic programming (ADP), a neuro-observer based online optimal control solution is developed for the finite-horizon optimal control problem of uncertain non-linear continuous-time systems. First, a neuro-observer is designed to estimate system states from the uncertain system without knowledge of system drift dynamics. Then based on the observed states, an online finite-horizon optimal control scheme is proposed by a single critic network to approximate the solution of the time-varying Hamilton-Jacobi-Bellman (HJB) equation and obtain the optimal control. In the design, a novel observer-critic architecture is presented for implementing the control scheme by using two neural networks (NNs): an observer NN is used to learn the uncertain system dynamics and a critic NN is employed not only to approximate the solution of time-varying HJB equation, but also to ensure the terminal constraint is satisfied. Besides, an additional adjusting term is introduced by Lyapunov theory in critic NN weight tuning algorithm, which relaxes the requirement for an initial stabilising control. Moreover, uniform ultimate bounded stability of the closed-loop system is guaranteed via Lyapunov's direct method. Finally, simulation results are shown to demonstrate the effectiveness of the proposed approach.

关键词： uncertain systems optimal control nonlinear systems continuous time systems dynamic programming time-varying systems Jacobian matrices observers Lyapunov methods closed loop systems neurocontrollers neuro-observer online finite-horizon optimal control uncertain nonlinear continuous-time systems closed-loop system stability weight tuning algorithm Lyapunov theory uncertain system dynamics neural networks observer-critic architecture time-varying Hamilton-Jacobi-Bellman equation system drift dynamics ADP adaptive dynamic programming

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stability limit of human-in-the-loop model reference adaptive control architectures

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INTERNATIONAL JOURNAL OF CONTROL 2018年第10期91卷 2314-2331页

作者： Yucelen, Tansel Yildiz, Yildiray Sipahi, Rifat Yousefi, Ehsan Nhan Nguyen Univ S Florida Dept Mech Engn Tampa FL 33620 USA Bilkent Univ Dept Mech Engn Ankara Turkey Northeastern Univ Dept Mech & Ind Engn Boston MA 02115 USA Natl Aeronaut & Space Adm Intelligent Syst Div Moffett Field CA USA

Model reference adaptive control (MRAC) offers mathematical and design tools to effectively cope with many challenges of real-world control problems such as exogenous disturbances, system uncertainties and degraded modes of operations. On the other hand, when faced with human-in-the-loop settings, these controllers can lead to unstable system trajectories in certain applications. To establish an understanding of stability limitations of MRAC architectures in the presence of humans, here a mathematical framework is developed whereby an MRAC is designed in conjunction with a class of linear human models including human reaction delays. This framework is then used to reveal, through stability analysis tools, the stability limit of the MRAC-human closed-loop system and the range of model parameters respecting this limit. An illustrative numerical example of an adaptive flight control application with a Neal-Smith pilot model is presented to demonstrate the effectiveness of developed approaches.

关键词： Uncertain dynamical systems model reference adaptive control human-in-the-loop systems closed-loop system stability human reaction time delay

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