Observer-Based H∞ Control for Networked Systems with Consecutive Packet Delays and Losses

Fuwen Yang,Yugang Niu,Wu Wang,Yongmin Li 제어·로봇·시스템학회 2010 International Journal of Control, Automation, and Vol.8 No.4

This paper considers the control problem for networked control systems (NCSs) with unreliable data communication. The unreliable data communication simultaneously exists in both control channel (from controller to actuator) and measurement channel (from sensor to controller) and may cause consecutive packet delays and losses. A new model is established based on all possible consecutive packet delays and losses. The observer-based controller is designed to exponentially stabilize the networked system in the sense of mean square, and also achieve the prescribed H∞ disturbance attenuation level. An iterative algorithm is developed to compute the optimal H∞ disturbance attenuation and the controller parameters by solving the semi-definite programming problem via interior-point approach. An illustrative example is provided to show the applicability of the proposed method.

Variational Bayesian Adaptive Unscented Kalman Filter for RSSI-based Indoor Localization

Bo Yang,Xinchun Jia,Fuwen Yang 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.3

Most existing localization schemes necessitate a priori statistical characteristic of measurement noise, which may be unrealistic in practical applications. This paper investigates the variational Bayesian adaptive unscented Kalman filtering (VBAUKF) for received signal strength indication (RSSI) based indoor localization under inaccurate process and measurement noise covariance matrices. First, an inaccurate and slowly varying measurement noise covariance matrix can be estimated by choosing appropriate conjugate prior distribution for an indoor localization model with inaccurate process and measurement noise covariance matrices. By choosing inverse Wishart priors distribution, the state, predicted error and measurement noise covariance matrices are inferred on each time separately. Second, a parameter optimization algorithm is designed to minimize the localization error of VBAUKF until it less than the threshold set in advance. Finally, experimental validation is presented to demonstrate the accuracy and effectiveness of the proposed filtering method for indoor localizaion.

Remote Localization of Network-based Automatic Guided Vehicles with a Novel Quantized Set-membership Approach

Hao Yang,Yilian Zhang,Wei Gu,Fuwen Yang 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.8

This paper investigates the remote localization problem for a network-based automatic guided vehicle (AGV) system. Considering the constraints of network bandwidth and the interference of unknown-but-bounded (UBB) noises, a novel quantized set-membership approach is proposed. First, a differential zooming strategy is designed for the quantization process of the measurement signals in order to reduce the quantization error and the negative influence of the quantization effects. Then, a remote modified set-membership filter is designed to eliminate the influence of UBB noises and obtain the optimal position state estimation ellipsoid for the considered AGV. Sufficient conditions for the existence of the set-membership filter are derived and a recursive algorithm is provided for computing the ellipsoid that guarantees to contain the true state. Finally, the remote localization performance analysis verifies the effectiveness of the proposed quantized set-membership approach for the considered AGV.

H∞ Control of LPV Systems with Randomly Multi-Step Sensor Delays

Yilian Zhang,Fuwen Yang,Qing-Long Han 제어·로봇·시스템학회 2014 International Journal of Control, Automation, and Vol.12 No.6

This paper is concerned with the H∞ control problem for a class of linear parameter-varying (LPV) systems with randomly multi-step sensor delays. A mathematical model which describes the randomly multi-step sensor delayed measurements for LPV systems is established. An improved Lyapunov func-tional is proposed to determine the asymptotically mean-square stability of the closed-loop system which depends on the varying parameters. The obtained full-order parameter-dependent dynamic feedback controller guarantees the considered system to be asymptotically mean-square stable and to satisfy the modified H∞ performance for all possible delayed measurements. An extended cone complementarity linearization method (CCLM) is used to solve the constrained linear matrix inequality (CLMI). Simulation results illustrate the effectiveness of the proposed method.

Simultaneous Stability of Large-scale Systems via Distributed Control Network with Partial Information Exchange

Yanfei Zhu,Fuwen Yang,Chuanjiang Li,Yilian Zhang 제어·로봇·시스템학회 2018 International Journal of Control, Automation, and Vol.16 No.4

This paper is concerned with the simultaneous stability of the multi-mode large-scale systems composed of the interaction subsystems. A novel distributed control network consisting of multiple network-based controllers with the partial information exchange is adopted to simultaneously stabilize the large-scale systems in multiple operation modes. In the distributed control network (DCN), a partial state information exchange approach is developed to save the real-time communication and computation resources. To compensate for the effects of dynamic couplings between interaction subsystems, the designed controllers use both the local states and the neighbors’ partial information with packet dropouts for local feedback design. Then, a series of Lyapunov functions are constructed to derive a matrix-inequality-based sufficient condition for the existence of the desired controllers. Based on an orthogonal complement technique, the gains of the controllers in DCN are parameterized. The iterative algorithm for the solution of simultaneous stabilization problem is also developed. Finally, a numerical example is performed to show the relevant feature of the proposed method.

Network-based Simultaneous H∞ Stabilization for Chemical Reaction Systems with Multiple Packet Dropouts

Yanfei Zhu,Fuwen Yang 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.1

In this paper, we study a novel control problem for network-based chemical reaction systems by virtueof a simultaneous H¥ stabilization methodology. In the presence of multiple packet dropouts, a finite collectionof stochastic parameter subsystems are extended to describe the networked control system (NCS). A single remotenetwork-based controller is designed to simultaneously stabilize the multiple stochastic parameter subsystems inthe sense of mean square and capture the H¥ control performance. Based on an orthogonal complement spacetechnique, a novel matrix inequality framework is established, where the controller gain is parametrized by theintroduction of a common free positive definite matrix, which is independent of the multiple Lyapunov matrices. Furthermore, an iterative linear matrix inequality (ILMI) algorithm is developed to deal with the proposedframework. Simulation results of a typical network-based chemical reaction system are provided to illustrate theeffectiveness of the proposed scheme.

State Estimation for Coupled Output Discrete-time Complex Network with Stochastic Measurements and Different Inner Coupling Matrices

Chun-Xia Fan,Fuwen Yang,Ying Zhou 제어·로봇·시스템학회 2012 International Journal of Control, Automation, and Vol.10 No.3

A state estimation problem is studied for a class of coupled outputs discrete-time networks with stochastic measurements, i.e., the measurements are missing and disturbed with stochastic noise. The considered networks are coupled with outputs rather than states, are coupled with different inner coupling matrices rather than identical inner ones. By using Lyapunov stability theory combined with stochastic analysis, a novel state estimation scheme is proposed to estimate the states of discrete-time complex networks through the available output measurements, where the measurements are stochastic missing and are disturbed with Brownian motions which are caused by data transmission among nodes due to communication unreliability. State estimation conditions are derived in terms of linear matrix inequalities (LMIs). A numerical example is provided to demonstrate the validity of the proposed scheme.

The application of a regularization method to the estimation of geometric errors of a three-axis machine tool using a double ball bar

Wenjie Tian,Guang Yang,Lina Wang,Fuwen Yin,Weiguo Gao 대한기계학회 2018 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.32 No.10

Geometric accuracy is crucially important for machine tools. Identification of geometric errors, especially position-dependent geometric errors, is still a challenging issue. This paper presents a systematic and fast approach to identify the geometric error components of a precision machine tool using double ball bar (DBB). The approach can be implemented in three steps: (1) polynomial based error modeling that relates the DBB radius error directly to the geometric error parameters of machine tool; (2) spatial measurement trajectory planning with a single installation of DBB in order to avoid producing extra setup errors; (3) error identification with regularization method that can solve the ill-posed identification problem effectively. Simulations and experiments show the accuracy and effectiveness of the proposed identification approach. The results of the DBB test show that, utilizing the proposed identification method, the roundness errors of the three circular paths in xy-, yz- and xz-plane are reduced from 27.3 μm, 20.7 μm and 24.1 μm to 9.2 μm, 12.3 μm and 7.8 μm, respectively, with error compensation.