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This paper considers the stabilization problem of nonlinear stochastic Hamiltonian systems with input time-varying delay. The systems under consideration are also subject to some small parameter perturbations in which are unavoidably involved. The dissipative structural properties of the Hamiltonian systems are fully considered and an observer-based adaptive controller are proposed to guarantee robustly...
This article investigates the problem of fault detection for a class of uncertain systems by a new method. Based on the system's own uncertainty and external disturbances, a more effective fault detection method is designed by the method of homogeneous polynomial function. This detection method not only suppresses the effects of disturbances and uncertainties on the residual signal but also makes...
The decentralized robust H-infinity and model predictive control problem for interconnected singular large-scale systems with uncertainty in states and control matrices is considered. Based on the bounded real lemma of singular systems, a sufficient condition for the existence of decentralized robust H-infinity and model predictive controller for uncertain singular large-scale systems is presented...
In this paper, we propose a predictor-based sliding mode control algorithm for LTI systems with input-delay and disturbance. It is shown that our proposed algorithm can completely reject the constant disturbance from the state channel. It is also shown that with our proposed algorithm, an enhanced disturbance rejection can be achieved for a large class of other time-varying disturbances. Simulations...
Scheduling production jobs in the real production system requires considering a number of factors which may prove to exert a negative effect on the production processes. Hence the need for the identification and compensation of potential disruptions as early as at the production planning stage. The aim of this paper is to employ the survival and the hazard function to anticipate potential disruptions...
Cloud scheduler manages multi-resources (e.g., CPU, GPU, memory, storage etc.) in cloud platform to improve resource utilization and achieve cost-efficiency for cloud providers. The optimal allocation for multi-resources has become a key technique in cloud computing and attracted more and more researchers' attentions. The existing multi-resource allocation methods are developed based on a condition...
The problem of spatial sensor location under parametric uncertainty of the repetitive distributed-parameter process is discussed. The idea is to reduce the uncertainty of the model used for the design of the iterative learning control, thus increasing the system performance. Particularly, an iterative scheme for estimation of the system parameter distributions is proposed based on the sequential experimental...
Reliability management is of great importance for the secure and sufficient operation of power systems, thus the n — KG — KL contingency constrained unit commitment (CCUC) problem is determined for investigation in this paper. In order to reveal the capability of different methods on the solution of CCUC, both explicit and implicit decomposition frameworks have been investigated, as well as their...
In this paper, we propose an optimization model for planning a robust path against changes in traffic volume. Robustness is based on the form of the travel time function. The proposed model can be applied not only when traffic volume increases but also when it decreases. In addition, the proposed model can set the ratio of consideration by a parameter depending on whether the traffic volume is increasing...
The presented work is motivated by Free Space Optics (FSO) communications. FSO is a well established wireless optical transmission technology considered as an alternative to radio communications for example in metropolitan wireless mesh networks. An FSO link is established by means of a laser beam between the transmitter and the receiver placed in the line of sight. A major disadvantage of FSO links...
In this paper, an enhanced form of modified Smith predictor (EMSP) is designed for the control of higher order stable systems. The higher order process, whose controller design is practically difficult, is reduced into first order plus delay (FOPDT) and second order plus delay (SOPDT) and thereby designing controllers capable to control servo and regulatory problems of its original higher order process...
An adaptive dynamic special global sliding mode controller which is based on proportional integral derivative (PID) sliding surface using radial basis function (RBF) neural network (NN) for a three-phase active power filter (APF) was presented in this paper. To overcome problems associated with schemes of the conventional sliding mode control, a global PID sliding manifold is introduced to realize...
In this paper, we propose a framework for robust distributed energy resource (DER) management in microgrids considering a retail electricity market. Our objective is to maximize the total profits of the microgrids while maintaining the reliability and security of the system. We formulate a two-stage robust optimization model to address uncertainties in day-ahead retail electricity price and DERs....
Disturbance Feedback Control (DFC) is a control technique that augments robustness of existing control systems with an extra feedback loop for the purpose of attenuation of disturbances and model errors. In this work, we propose a DFC design method based on output feedback control via Linear Matrix Inequalities (LMIs). A parametric uncertainty model is used to represent mismatches between a nominal...
This paper presents a fuzzy gain scheduling PID controller for a gimbal stabilization platform. A fuzzy method is used to calculate the main controller parameters based on the close loop error, as well as its derivative. A comparison between this method and other conventional controllers used for this application is made focused on robust stability. Finally, a complete implementation over an embedded...
State of the art computer-aided control system design (CACSD) tools for robust control offer only very basic commands and consequently require a very detailed mathematical background and advanced user knowledge about syntax and data structures. Also many typical controller design problems have to be reformulated over and over. This contribution therefore aims to tackle these matters by introducing...
The focus of this paper is on the design of input shapers for systems with uncertainties in the parameters of the vibratory modes which need to be attenuated. A probabilistic framework is proposed for the design of the robust input shaper, when the uncertain modal parameters are characterized by probability density functions. A convex chance constrained optimization problem is posed to determine the...
Energy storage is an important resource that can balance fluctuations in energy generation from renewable energy sources, such as wind, to increase their penetration. Many existing storage control methods require perfect information about the probability distribution of uncertainties. In practice, however, the distribution of renewable energy production is difficult to reliably estimate. To resolve...
This study is aimed to find low order, stable and proper controllers for the linearized models of two well known underactuated robots i.e. Acrobot and Pendubot around their upright equilibrium points in order to maximize the robustness of the feedback loop to uncertainties. The proposed method makes use of the robust stabilization of finite dimensional plants by Nevanlinna-Pick interpolation problem...
Disturbance Feedback Control (DFC) is a technique in which an existing controller is augmented with an additional loop. It was originally proposed by Fuji Electric in 1980, and has been applied in Factory Automation (FA). This paper proposes a robust DFC including the anti-windup controllers for process control. The proposed method is designed in two steps; firstly, the robust DFC without saturation...
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