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Chen Hui - IEEE Xplore Author Profile

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The order of an aggregated Markov model (AMM) is an index of complexity and is closely related to the reachable subspace of a model. The AMM is called reachable-space reducible when the reachable subspace is not the whole space. Previous results demonstrate that there exists a reduced-order quasi-realization, which may not satisfy the nonnegative constraints, equivalent to a given reachable-space ...Show More
We set up a continuous-time data-driven control framework based on sampling linear functionals. Under some recently established sufficient conditions for informativity for system identification, we give data-based solutions to stabilization and optimal quadratic regulation problems.Show More
We establish formulas relating the state of a continuous-time system with that of the transformed one in a Takenaka–Malmquist–Kautz orthogonal basis. We use such relation to give a simple proof that if the original system is dissipative, then the transformed one is also dissipative with the same storage function. We apply our results to continuous-time subspace system identification.Show More
The order of a hidden Markov model (HMM) is an index of the complexity and is closely related to the reachable subspace in the state of the model. When the reachable subspace is not the whole space, there exists a reduced-order quasi hidden Markov model (quasi-HMM), which may not satisfy the nonnegative constraints, equivalent to the original HMM. Such an HMM will be called reachable-space reducib...Show More
The Wiener process has provided a lot of practically useful mathematical tools to model stochastic noise in many applications. However, this framework is not enough for modeling extremal events, since many statistical properties of dynamical systems driven by the Wiener process are inevitably Gaussian. The goal of this work is to develop a framework that can represent a heavy-tailed distribution w...Show More
In order to solve environmental issue and energy crisis, PV (photovoltaic) generation has experienced the most growth among the renewable energy sources in the last few years, and the interconnection capacity of PV generation may continue to increase. However, the more recently special problem in Japan, the capacity of qualified PV generation facilities exceeds the allowable interconnection capaci...Show More
PV (photovoltaic) generation has experienced the most growth among the renewable energy sources in the last few years, and the interconnection capacity of PV generations may continue to increase. However, more recently special problem in Japan, the capacity of qualified PV generation facilities exceeds the allowable interconnection capacity determined by each power grid company. This fact is recog...Show More
A Bayesian approach for system identification using kernel functions is a popular method. The kernel functions are considered as certain prior knowledge about a target system, so selecting proper kernels is required. Recent studies show that it is successful to use OBF-s(orthonormal basis function)-based kernels as the kernel functions, but estimating hyper-parameters of the kernel functions is a ...Show More
Unpredictable accidents and uncertain environment make the management of the power systems difficult, which may increase the cost of power generation. In this paper, we apply a stochastic model predictive control to maintain the demand-and-supply balance in the IEEE 30-bus system and analyze how much a transmission line fault with uncertain weather forecast raises the generation costs. Since the t...Show More
PV (photovoltaic) generation may cause voltage rise at the interconnection point due to reverse power flow, which is recognized as a critical issue for keeping power quality. This paper investigates a decentralized management problem of PCSs (Power Conditioning Systems) which are used to interconnect the PV system into the power grid. We consider a real-time pricing strategy of the operator who pl...Show More
Photovoltaic (PV) generation may cause a voltage rise at the interconnection point due to reverse power flows, and it is recognized as a critical issue for keeping power quality. This paper investigates a decentralized management problem of power conditioning systems (PCSs), which are used to interconnect the PV system into the power grid. We consider a real-time pricing strategy of the operator, ...Show More
In this paper, we focus on one of the motion coordination problems called attitude synchronization. We propose a continuous-time protocol to align the states of a network of agents evolving in the space of rotations SO(3). Our work is related to the Riemannian consensus, which is a general extension of classical consensus algorithms to Riemannian manifolds. The existing algorithms have the problem...Show More
Global warming and the depletion of fossil fuels encourage installing a large scale PV (photovoltaic) system. The large scale PV system may cause a issue of the voltage rise at an interconnection point due to the reverse power flow. This paper investigates the distributed management problem of PCSs (power conditioning systems) which are used to interconnect the PV system to the power gird. We cons...Show More
This paper investigates the distributed voltage control problem of a distribution power grid in which a voltage rise occurs due to reverse load flow from distributed generators. A centralized operation to regulate the grid voltage becomes difficult, since the number of distributed generators involved is large. This paper considers a real-time pricing strategy and distributed optimization by each d...Show More
The Wiener process has provided lots of practically useful mathematical tools to model stochastic noise in many applications. However, this framework is not enough for modeling extremal events since many statistical properties of dynamical systems driven by Wiener processes are inevitably Gaussian. The goal of this work is to develop a framework that can represent heavy tailed distribution without...Show More
This paper shows a limitation of signal-to-noise ratio (SNR) for amplitude-bounded noise in control of linear discrete-time systems over channels with feedback. The SNR allowed in stabilizing the closed-loop system is shown to depend on the product of unstable poles of the plant. The control law for minimizing the SNR is constructed from state-feedback controller and two observers employed in the ...Show More
This paper presents an SNR limitation in control under amplitude-bounded noise. The SNR of feedback link in control system is evaluated with respect to amplitude and minimized over all causal control laws. The minimum SNR is represented by the absolute value of the product of unstable poles of the plant. This index is known to describe performance limitations in various control problems. The optim...Show More
This paper proposes a novel approach for the controller design of a three-phase grid-tie inverter. First, the paper analyzes the input-output map of the system consisting of the cascade connection of a diagonal transfer function pre- and post-multiplied by DQ (direct-quadrature) and inverse DQ transformations which are prevalently used as a controller for systems with a rotating axis. It shows tha...Show More
This paper deals with the problem of model identification in continuous-time using subspace techniques. More precisely, a recently presented continuous-time predictor-based subspace identification algorithm which relies on a system transformation using the Laguerre basis is considered and a bootstrap-based approach to the problem of quantifying the variance error associated with the identified mod...Show More
Given an inner function, the orthogonal complement of the corresponding shift invariant subspace induces a system transformation for linear time-invariant systems, which is a generalization of the lifting technique for the sample-data control and Hambo-transform in the sense the inner function is arbitrary. This paper extends the transformation for systems with unstable eigenvalues, and derives a ...Show More
This paper deals with the problem of model identification in continuous-time using subspace techniques. More precisely, a recently presented continuous-time predictor-based subspace identification algorithm which relies on a system transformation using the Laguerre basis is considered and a recursive counterpart is developed.Show More
This paper studies a continuous-time system identification method based on system transformation using generalized orthonormal basis functions, especially the Laguerre basis. It is known that the expansion of observation signals with Laguerre basis functions is useful for analyzing linear dynamical systems. This processing however, involves the calculation with infinite integral, hence, the proble...Show More
This paper considers control design problems for a robotic manipulator that is used for handling silicon semiconductor wafers, and how to reduce the throughput time of the total task of the manipulator. In this paper, we propose discontinuous switchings of controllers which are already designed and realize appropriate motions for each translatory and rotational motions. We show that such a control...Show More
This paper applies the abstract linear programming approach to the LQ control problem for continuous-time constrained systems. A gap-free dual problem is derived with the property that it can be approximated by finite dimensional convex programming. The structure of the dual variables is scrutinized. An example is included to show the limitation of control performance in the presence of right-half...Show More
Continuous-time system identification is desirable and necessary from several fine characteristics of continuous-time models. It was already shown that a continuous-time system is identified effectively by means of the transformation of the continuous-time system into a discrete-time system using the generalized orthonormal basis. This paper proposes the error analysis of continuous-time system id...Show More