Zhicheng Li

Cooperative Control of Distributed Energy Storage Systems in a Microgrid

Energy storage systems (ESSs) are often proposed to support the frequency control in microgrid systems. Due to the intermittency of the renewable generation and constantly changing load demand, the charging/discharging of various ESSs in an autonomous microgrid needs to be properly coordinated to ensure the supply-demand balance. Recent research has discovered that the charging/discharging efficiency of ESSs has remarkable dependence on the charging/discharging rate and state-of-charge of the ESS. This paper proposes a distributed cooperative control strategy for coordinating the ESSs to maintain the supply-demand balance and minimize the total power loss associated with charging/discharging inefficiency. The effectiveness of the proposed approach is validated by simulation results.

Improved H∞ filter design for discrete-time Markovian jump systems with time-varying delay

Abstract This paper is concerned with the H ∞ filter design for a class of discrete-time Markovian jump systems with time-varying delay. By constructing an appropriate Lyapunov–Krasovskii functional and applying Wirtinger-based inequality for discrete-time context combined with reciprocally convex approach, an improved stability criterion is obtained. Then a delay-dependent H ∞ performance condition is achieved for the system. Moreover, a desired filter is constructed based on the performance analysis, which guarantees the filtering error system to be stochastically stable and satisfying a prescribed H ∞ performance level. In the end, some numerical examples are provided to illustrate the effectiveness and superiority of the new criterion.

A novel approach to stability analysis for switched positive linear systems

Abstract This paper is concerned with exploring less conservative stability conditions for a class of switched positive linear systems. A switched matrix-parameterized copositive Lyapunov function (SMPCLF) is first introduced, where “matrix-parameterized” implies that the parameters of the constructed Lyapunov function are distributed in a matrix, which is different from the traditional vector-parameterized copositive Lyapunov function. Based on the proposed SMPCLF, a new stability criterion is derived for the underlying systems under arbitrary switching. Furthermore, by performing higher order relaxations in the SMPCLF and its time difference by positive states, the conservativeness can be further reduced. A numerical example is given to demonstrate the effectiveness and advantages of the obtained theoretical results.

Exponential stability analysis and stabilization of switched delay systems

Abstract This paper investigates the problems of exponential stability analysis and stabilization for switched systems with time-varying delay via a new approach. To study the problems, the original system is transformed into an interconnection system, which is composed of a feedback subsystem and a forward one with a constant delay and an uncertainty disturbance. The exponential stability condition is presented to guarantee the α-input–output stability of the interconnection system based on the scaled small gain theorem, which is further proved to guarantee the exponential stability of the original system under arbitrary switching signal. Then the switching law existence condition is also proposed for exponential stabilization without input signal. Moreover, the problem of stabilization is further solved with admissible controllers obtained via convex optimizations. Both the problems are solved based on the model transformation method and the input–output approach. The merit of the proposed results lies in its reduced conservatism, which is made possible by a precise approximation of the time-varying delay and the scaled small gain theorem. The superiority and effectiveness of our results over the existing ones are illustrated via some numerical examples.

Further result on H∞ filter design for continuous-time Markovian jump systems with time-varying delay

Abstract This paper investigates the problem of H ∞ filtering for Markovian jump linear systems with time-varying delay. The aim of this problem is to design an H ∞ filter that ensures stochastic stability of the filtering error system and a prescribed L2-induced gain from the noise signals to the estimation error, for all admissible uncertainties. For solving the problem, we transform the system under consideration into an interconnection system. Based on the system transformation and the stochastic scaled small gain theorem, stochastic stability of the original system is examined via the stochastic stability version of the bounded realness of the transformed forward system. The merit of the proposed approach lies in its reduced conservatism, which is made possible by a precise approximation of the time-varying delay and the stochastic scaled small gain theorem. The proposed H ∞ filtering condition is demonstrated to be less conservative than most existing results. Moreover, the H ∞ filter design condition is further presented via convex optimizations, whose effectiveness are also illustrated via numerical examples.

Compressed Sensing via Dictionary Learning and Approximate Message Passing for Multimedia Internet of Things

In this paper, we present a compressed sensing-based approach, which combines the dictionary learning (DL) method and the approximate message passing (AMP) approach. The approach can be used for efficient communication in the multimedia Internet of Things (IoT). AMP is a signal reconstruction algorithm framework, which can be explained as an iterative denoising process. On the other hand, the DL method seeks an adaptive dictionary for realizing sparse signal representations, and provides good performance in signal denoising. We apply the DL-based denoising method within the AMP algorithm framework and propose a novel DL-AMP framework. We demonstrate our framework’s effectiveness for multimedia IoT devices by showing its capability in reducing required communication bandwidth for multimedia communication while improving reconstruction quality (by over 2 dB).

On Finite frequency H∞ performance for discrete linear time delay systems

ABSTRACT This paper is concerned with the finite frequency H∞ performance of discrete linear systems with time delay. The disturbance of the system is considered to be restricted in low/middle/high frequency. A novel summation inequality is proposed by including more free weighed matrices. Then by using generalised Kalman–Yakubovich–Popov Lemma and a Lyapunov–Krasovskii functional like method, a new bounded real lemma is presented for the finite frequency H∞ performance analysis. The advantages and reduced conservatism of the new criterion are illustrated by a classical example from the literature.

ECG signal compressed sensing using the wavelet tree model

Compressed Sensing (CS) is a novel approach of compressing, which can reconstruct a sparse signal much below Nyquist rate of sampling. Though ECG signals can be well approximated by some wavelet basis, the noise still influences the ECG wavelet decomposition and also reduces the effectiveness of the signal reconstruction. In this note, we present a compressed sensing method to reconstruct ECG signals in MITBIH [1] arrhythmia based on different wavelet families. Our approach is composed of two steps. The first step is to use Condensing Sort and Select Algorithm (CSSA) to dampen the impact of the noise for ECG signals and get sparse signals to estimate and replace raw ECG signals, and then, the second step is to use CS method to compress and transfer those filtered signals. The result is evaluated by some indices like Percentage Root Mean Square Difference (PRD), Mean Square Error (MSE), Peak Signal To Noise Ratio (PSNR), and Correlation Coefficient (CoC). These reconstructed results are comprehensively compared by 4:1 compression ratio. These results indicate that Symlets and Daubechies wavelet families have better performance for all parameters compared to other wavelet families and most of existing results.

Distributed Robust Control Strategy of Grid-Connected Inverters for Energy Storage System’s State-of-Charge Balancing

Battery energy storage system (BESS) plays an important role in enhancing system flexibility, stability, and reliability of the power grid. This paper proposes a fully distributed two-level control strategy of the grid-connected inverters for BESSs. The upper-level control determines the charging/discharging power references for the BESS units according to the state of charge levels and the supply demand balance among intermittent distributed generations and time-varying load demands. The lower-level control adopts the proposed discrete robust control algorithm which enables the BESS to track the power references accurately. The uncertainty and disturbance are estimated by the disturbance estimation technique and the chattering problem is alleviated by introducing a saturation function. The convergence and stability of the proposed distributed control strategy are guaranteed through rigorous analysis and the effectiveness is validated by simulation results.

Robust Hinf Control of Theodorsen’s Lift Model for a Pitching and Plunging Airfoil Using LMI Approach

This paper develops a robust H controller for a pitching and plunging airfoil using the state space representation of Theodorsen’s lift model employing the linear matrix inequalities (LMI) method. Both parameter uncertainty and the input disturbances are considered in the model. The existence condition for the robust H state-feedback controller is obtained using the Lyapunov functional approach. In practical systems, it is difficult to obtain all the states of the model needed for the controller. Thus the observer existence condition is proposed to provide the states’ information for the model. Several examples are used to demonstrate the effectiveness of the designed controller and the designed observer.