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constrained adaptive neural network control of an MIMO aeroelastic system with input nonlinearities

第三十九届中国控制会议

作者： Xuemei Li Xinge Liu School of Mathematics and Statistics Central South University

In this paper, the null controllability of the fractional impulsive delayed systems in the finite dimensional space has been considered. Sufficient conditions are derived for the null-controllability of linear and nonlinear impulsive delayed systems with the values of the control function u in an m-dimensional unit cube. Further, Schauder fixed point theorem is used to prove the null controllability of nonlinear system with constrained control. Finally, examples are provided to illustrate the obtained results.

关键词： Null controllability Fractional Impulsive systems constrained control Fixed point

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Chinese Journal of Aeronautics 2017年第2期30卷 796-806页

作者： Gou Yiyong Li Hongbo Dong Xinmin Liu Zongcheng Aeronautics and Astronautics Engineering College Air Force Engineering University Xi'an 710038 China

A constrained adaptive neural network control scheme is proposed for a multi-input and multi-output（MIMO） aeroelastic system in the presence of wind gust,system uncertainties,and input nonlinearities consisting of input saturation and *** regard to the input nonlinearities,the right inverse function block of the dead-zone is added before the input nonlinearities,which simplifies the input nonlinearities into an equivalent input *** deal with the equivalent input saturation,an auxiliary error system is designed to compensate for the impact of the input ***,uncertainties in pitch stiffness,plunge stiffness,and pitch damping are all considered,and radial basis function neural networks（RBFNNs） are applied to approximate the system *** combination with the designed auxiliary error system and the backstepping control technique,a constrained adaptive neural network controller is designed,and it is proven that all the signals in the closed-loop system are semi-globally uniformly bounded via the Lyapunov stability analysis ***,extensive digital simulation results demonstrate the effectiveness of the proposed control scheme towards flutter suppression in spite of the integrated effects of wind gust,system uncertainties,and input nonlinearities.

关键词： Aeroelastic system constrained control Flutter suppression Input nonlinearities RBFNNs

Output constrained IMC controllers in control systems of electromechanical actuators

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control Theory and Technology 2015年第3期13卷 245-255页

作者： Piotr M.MARUSAK Suwat KUNTANAPREEDA Institute of control and Computation Engineering Warsaw University of Technology Faculty of Engineering King Mongkut's University of Technology North Bangkok

Electromechanical actuators are widely used in many industrial applications. There are usually some constraints existing in a designed system. This paper proposes a simple method to design constrained controllers for electromechanical actuators. The controllers merge the ideas exploited in internal model control and model predictive control. They are designed using the standard control system structure with unity negative feedback. The structure of the controllers is relatively simple as well as the design process. The output constraint handling mechanism is based on prediction of the control plant behavior many time steps ahead. The mechanism increases control performance and safety of the control plant. The benefits offered by the proposed controllers have been demonstrated in real-life experiments carried out in control systems of two electromechanical actuators： a DC motor and an electrohydraulic actuator.

关键词： constrained control internal model control (IMC) model predictive control (MPC) electromechanical actuators

Disturbance rejection tube model predictive levitation control of maglev trains

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High-Speed Railway 2024年第1期2卷 57-63页

作者： Yirui Han Xiuming Yao Yu Yang School of Automation and Intelligence Beijing Jiaotong UniversityBeijing 100044China

Magnetic levitation control technology plays a significant role in maglev *** a controller for the levitation system is challenging due to the strong nonlinearity,open-loop instability,and the need for fast response and *** this paper,we propose a Disturbance-Observe-based Tube Model Predictive Levitation control(DO-TMPLC)scheme combined with a feedback linearization strategy for the levitation *** proposed strategy incorporates state constraints and control input constraints,i.e.,the air gap,the vertical velocity,and the current applied to the coil.A feedback linearization strategy is used to cancel the nonlinearity of the tracking error ***,a disturbance observer is implemented to actively compensate for disturbances while a TMPLC controller is employed to alleviate the remaining ***,we analyze the recursive feasibility and input-to-state stability of the closed-loop *** simulation results indicate the efficacy of the proposed control strategy.

关键词： Maglev trains Levitation system constrained control Disturbance observer Model predictive control

constrained nonlinear MPC for accelerated tracking piece-wise references and its applications to thermal systems

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control Theory and Technology 2022年第1期20卷 69-79页

作者： Defeng He Qingsong Wang Ping Han Haiping Du College of Information Engineering Zhejiang University of TechnologyHangzhou310023ZhejiangChina School of Electrical Computer and Telecommunications EngineeringUniversity of WollongongWollongongNSW2522Australia

In this paper,we propose a model predictive control(MPC)strategy for accelerated offset-free tracking piece-wise constant reference signals of nonlinear systems subject to state and control *** special contractive constraints on tracking errors and terminal constraints are embedded into the tracking nonlinear MPC ***,recursive feasibility and closed-loop convergence of the tracking MPC are guaranteed in the presence of piece-wise references and constraints by deriving some sufficient ***,the local optimality of the tracking MPC is achieved for unreachable output reference *** comparing to traditional tracking MPC,the simulation experiment of a thermal system is used to demonstrate the acceleration ability and the effectiveness of the tracking MPC scheme proposed here.

关键词： Model predictive control Nonlinear systems constrained control Tracking control Thermal systems

Fixed-time constrained acceleration reconstruction scheme for robotic exoskeleton via neural networks

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Frontiers of Information Technology & Electronic Engineering 2020年第5期21卷 705-722页

作者： Tao XUE Zi-wei WANG Tao ZHANG Ou BAI Meng ZHANG Bin HAN Department of Automation Tsinghua UniversityBeijing 100084China Department of Electrical and Computer Engineering Florida International UniversityMiami 33174USA Move Robotics Technology Co. Ltd.Shanghai 201306China School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China

Accurate acceleration acquisition is a critical issue in the robotic exoskeleton system,but it is difficult to directly obtain the acceleration via the existing sensing *** existing algorithm-based acceleration acquisition methods put more attention on finite-time convergence and disturbance suppression but ignore the error constraint and initial state irrelevant *** this end,a novel radical bias function neural network(RBFNN)based fixed-time reconstruction scheme with error constraints is designed to realize high-performance acceleration *** this scheme,a novel exponential-type barrier Lyapunov function is proposed to handle the error *** also provides a unified and concise Lyapunov stability-proof template for constrained and non-constrained ***,a fractional power sliding mode control law is designed to realize fixed-time convergence,where the convergence time is irrelevant to initial states or external disturbance,and depends only on the chosen *** further enhance observer robustness,an RBFNN with the adaptive weight matrix is proposed to approximate and attenuate the completely unknown *** simulation and human sub ject experimental results validate the unique properties and practical robustness.

关键词： Acceleration reconstruction Fixed-time convergence constrained control Barrier Lyapunov function Initial state irrelevant technique Robotic exoskeleton

Limit protection design in turbofan engine acceleration control based on scheduling command governor

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Chinese Journal of Aeronautics 2021年第10期34卷 67-80页

作者： Wenhao XU Jinquan HUANG Jiakun QIN Muxuan PAN College of Energy and Power Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China

A new limit protection method based on Scheduling Command Governor(SCG) is proposed for imposing multiple constraints on a turbofan engine during acceleration process. A Gain Scheduling controller(GSC) is designed for the transient state control and its stability proof is developed using Linear Matrix Inequalities(LMIs). The SCG is an add-on control scheme which manages engine limits effectively based on reference trajectory optimization. Unlike the traditional min–max architecture with switching logic, the SCG method utilizes the Linear Parameter Varying(LPV) closed-loop model to form a prediction of future constraint violation and per instant solves a constraint-admissible reference within an approximate Maximal Output Admissible Set(MOAS).The influence of the variation of engine dynamic characteristics and equilibrium points during transient state control is handled by the design of contractive sets. Simulation results on a turbofan engine component-level model show the applicability and effectiveness of the SCG method. Compared to the traditional min–max method, the SCG method has less conservativeness. In addition,the design of contractive sets makes conservativeness tunable.

关键词： Command governors constrained control Contractive sets Gain scheduling Limit protection LPV model Turbofan engines

Time-Varying Asymmetrical BLFs Based Adaptive Finite-Time Neural control of Nonlinear Systems With Full State Constraints

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IEEE/CAA Journal of Automatica Sinica 2020年第5期7卷 1335-1343页

作者： Lei Liu Tingting Gao Yan-Jun Liu Shaocheng Tong College of Science Liaoning University of TechnologyJinzhou 121001China IEEE

This paper concentrates on asymmetric barrier Lyapunov functions(ABLFs)based on finite-time adaptive neural network(NN)control methods for a class of nonlinear strict feedback systems with time-varying full state *** the process of backstepping recursion,the approximation properties of NNs are exploited to address the problem of unknown internal *** ABLFs are constructed to make sure that the time-varying asymmetrical full state constraints are always *** to the Lyapunov stability and finitetime stability theory,it is proven that all the signals in the closedloop systems are uniformly ultimately bounded(UUB)and the system output is driven to track the desired signal as quickly as possible near the *** the meantime,in the scope of finitetime,all states are guaranteed to stay in the pre-given ***,a simulation example is proposed to verify the feasibility of the developed finite time control algorithm.

关键词： Barrier Lyapunov functions constrained control finite time stability neural control

Dual-mode Nonlinear MPC via Terminal control Laws With Free-parameters

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IEEE/CAA Journal of Automatica Sinica 2017年第3期4卷 526-533页

作者： Defeng He College of Information Zhejiang University of TechnologyHangzhou 310023China

The paper presents a new dual-mode nonlinear model predictive control(NMPC) scheme for continuous-time nonlinear systems subject to constraints on the state and *** idea of control Lyapunov functions for nonlinear systems is used to compute the terminal regions and terminal control laws with some free-parameters in the dual-mode NMPC *** parameters of the terminal controller are selected offline to estimate the terminal region as large as possible;and the parameters are optimized online to gain optimality of the terminal controller with respect to given cost *** a dual-mode NMPC algorithm with varying time-horizon is formulated for the constrained *** feasibility and closed-loop stability of this NMPC are *** example of a spring-cart is used to demonstrate the advantages of the presented scheme by comparing to the dual-mode NMPC via the linear quadratic regulator(LQR) method.

关键词： constrained control dual-mode control model predictive control nonlinear control