Publications

This paper addresses the problem of state and fault estimation for linear continuous-time systems with actuator failures. A new estimation technique is presented to deal with this design problem. In the proposed approaches, the original system is first augmented in a descriptor system, and a new sliding mode observer is introduced to obtain accurate estimations of both system states and actuator faults. A numerical example is presented to illustrate the effectiveness and applicability of the proposed technique.

In real engineering environments, the time-varying speed condition is very common. However, most fault diagnosis methods take the constant speed into account, thus ignoring the fault signal changes under time-varying speeds. In this paper, we propose a weighted feature fusion framework based on convolutional neural network (CNN) and graph convolutional network (GCN) to achieve mechanical fault diagnosis. First, CNNs and GCNs are adopted to extract graph and long-range features. Then, a weighted fusion strategy is utilized to integrate the output of the two networks to obtain more diagnostic results. Finally, extensive experiments conducted on a time-varying speed dataset are used to validate the superiority and effectiveness of the proposed method compared to the other methods.

This paper presents an application of radial basis function (RBF) in the identification and control design of transverse flux machines as nonlinear systems with unknown nonlinearity part. The technique of feedback linearization and H/sub /spl infin// control are used to design an adaptive control law for compensating the unknown nonlinearity part, such that the effect of the cogging torque as a disturbance is decreased into the angle and angular velocity tracking.

This paper studies a class of stochastic systems with multiple disturbances which include the disturbance with partially-known information and the white noise. A disturbance observer is constructed to estimate the disturbance with partially-known information, based on which, a disturbance observer-based disturbance attenuation control (DOBDAC) scheme is proposed by combining pole placement and linear matrix inequality (LMI) methods.

The non-fragile sliding mode tracking control design problem for a flexible air-breathing hypersonic vehicles (FAHVs) is investigated in this paper. A linearized model is constructed with respect to a trim point for the nonlinear, dynamically coupled simulation model of the FAHVs with external disturbance, then a reference model is designed and a tracking error model is proposed. An integral sliding surface is designed, and then the non-fragile H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> controller design problem for the sliding mode dynamics is discussed. sufficient condition is derived for the existence of such a controller in the presence of unmatched disturbance. A SMC law is derived to guarantee the reachability of the specified sliding surface. Finally, An illustrative simulation on the nonlinear dynamics of FAHVs is given to show the effectiveness of the proposed control methods.

In this paper, a control strategy to mitigate the vibrational response of adjacent buildings under seismic excitation is presented. The proposed strategy combines inter building passive actuators with active actuators placed in the building stories. The main ideas are presented by means of a simplified two-building model; however, a semi-decentralized overlapping approach via the inclusion principle has been used to impose a proper information exchange structure suitable for wireless control of large buildings. Numerical simulations have been carried out to assess the performance of the proposed methodology with promising results. The overall control system exhibits some degree of fault-tolerance since only partial degradation of the control performance results from partial failures of the control system.

This paper is concerned with the mobile robot localization problem subject to filter gain uncertainty under dynamic event‐triggered communication mechanism, and meanwhile, the H ∞ filtering performance and the error variance constraint are guaranteed. For saving the sensor energy, a dynamic event‐triggered communication mechanism is introduced to manage the transmission of the measurement data from the sensor to the filter. To characterize the possible fluctuations of the desired filter gain, a resilient filter is constructed for the mobile robot localization. The aim of this paper is to find a solution to the mobile robot localization problem by designing a nonlinear resilient filter such that the filtering error dynamics satisfies both the H ∞ performance requirement and the error variance constraint over a finite time horizon simultaneously. By resorting to the Lyapunov theory and the stochastic analysis technique, the sufficient conditions are established to guarantee that the error dynamic system satisfies both the H ∞ performance requirement and the error variance constraint. Then, a recursive linear matrix inequality (RLMI) approach is employed to design the desired filter. Based on the proposed filter design scheme, the corresponding localization algorithm is presented. Finally, an experiment is conducted in the simulation environment to verify the effectiveness of the proposed localization algorithm.

This paper studies delay-dependent exponential dissipative and l2 - l∞ filtering problems for discrete-time switched neural networks (DSNNs) including time-delayed states. By introducing a novel discrete-time inequality, which is a discrete-time version of the continuous-time Wirtinger-type inequality, we establish new sets of linear matrix inequality (LMI) criteria such that discrete-time filtering error systems are exponentially stable with guaranteed performances in the exponential dissipative and l2 - l∞ senses. The design of the desired exponential dissipative and l2 - l∞ filters for DSNNs can be achieved by solving the proposed sets of LMI conditions. Via numerical simulation results, we show the validity of the desired discrete-time filter design approach.

Based on analyzing principle about the smart car’s speed control system, the system mathematical model is built. Considering the control optimization, a novel control scheme is proposed based on internal model control, and the internal model controller of speed control system is established. Regarding this subject, the internal control theory is introduced to verify the control performance; the traditional PID control method is employed in the experiment. The experiment indicates that the proposed method based on internal model control is easier to determine parameter and has a well robust and good control result of smart car’s speed.

Digitization and digitalization have already changed our world significantly.Further disruptions are imminent with the ongoing digital transformation, a major component of which is digital twins.As the big data techniques, Internet of Things, cloud computing, and artificial intelligence algorithms advance, the digital twin technology has entered a phase of rapid development.It has been stated to be one of the top ten most promising technologies.Although it is still in its early stages, digital twins are already being widely used in a variety of fields, especially in industry, smart cities, and smart health, which are points that attract most researchers to study.In the literature, there can be seen numerous articles and reviews on digital twins, published every year in these three fields.It is therefore timely, even necessary, to provide an analysis of the published work.This is the motivation behind this article, the focus of which is the major research and application areas of digital twins.The survey first analyzes the recent developments of digital twins, then summarizes the theoretical underpinnings of the technology, and finally concludes with specific developments in various application areas of digital twins.It also discusses the challenges that may be encountered in the future.

This paper studies the problems of stability and stabilization for a class of singular switching semi-Markovian jump systems. The general transition rates in the semi-Markov process cover completely unknown and uncertain bounded as two special cases. First, sufficient conditions are developed to ensure the unforced system to be regular, impulse-free, and exponentially mean-square stable. Then, by proposing a state feedback controller, sufficient conditions in terms of strict linear matrix inequalities are derived to guarantee the closed-loop system to be stochastically stabilziable. Finally, a numerical example is provided to show the effectiveness of the obtained results.

This paper proposes a numerical approach for finding an optimal control based on wavelet functions for vibration reduction of a base-isolated building subjected to actual earthquakes. The objective is two-fold: (1) to find a computational method using properties of Haar functions, and (2) to calculate controller gains approximately by solving only algebraic equations instead of solving the Riccati differential. Simulation results are included to demonstrate the validity and applicability of the technique.

This paper presents an application of wavelet networks (WNs) in identification and control design for a class of structures equipped with a type of semiactive actuators, which are called magnetorheological (MR) dampers. The nonlinear model is identified based on a WN framework. Based on the technique of feedback linearization, supervisory control and H ∞ control, an adaptive control strategy is developed to compensate for the nonlinearity in the structure so as to enhance the response of the system to earthquake type inputs. Furthermore, the parameter adaptive laws of the WN are developed. In particular, it is shown that the proposed control strategy offers a reasonably effective approach to semiactive control of structures. The applicability of the proposed method is illustrated on a building structure by computer simulation.

In this work, we present a new and effective method to design discrete-time static output-feedback H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controllers. This new method, based on a Linear Matrix Inequality (LMI) formulation, introduces a suitable transformation of the LMI variables that allows to obtain an explicit expression for the output-feedback gain matrix. Moreover, for problems involving a set of subsystems with information exchange constraints, a convenient structure on the LMI variables can be imposed in order to design semi-decentralized controllers, where the corresponding output-feedback gain matrix has a prescribed zero-nonzero structure. To illustrate the proposed methodology, discrete-time static velocity-feedback H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controllers to mitigate the seismic response of a five-story building are designed. In particular, two different designs are presented: (i) a centralized controller that requires all the inter-story velocities to compute the control actions, and (ii) a semi-decentralized controller that can operate using only the inter-story velocities of neighboring floors.