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This paper presents a decentralized method to the problem of multiple unmanned aerial vehicles (UAVs) cooperative search of an unknown area. Firstly, based on search map model, the multiple UAVs cooperative search problem is posed as a receding horizon (RH) optimization decision problem, and a RH based UAV search decision process is proposed. Then, this centralized online optimization problem is partitioned...
This paper presents a Jacobi iterative based computational paradigm for solving the data regression in wireless sensor networks (WSNs). The in-network computational scheme is proposed to construct a mixture regression model through the cluster-based Jacobi distributed iteration, where the intersections among mixture structure of regression model are decoupled through a new cluster-based message passing...
In practical applications, it is often encountered that the jump modes of a Markovian jump linear system may not be fully accessible to the filter, and thus designing a filter which partially or totally independent of the jump modes becomes significant. In this paper, by virtue of a new stability and Hinfin performance characterization, a novel necessary and sufficient condition for the existence...
This paper deals with the problem of Hinfin norm computation for general symmetric systems and descriptor symmetric systems. The computation of Hinfin norm for state-space symmetric systems is extended to descriptor symmetric systems. An explicit expression is given based on the bound real lemma (BRL), and the generalized bound real lemma (GBRL). The results have obvious computational advantages,...
Motion control systems have found their application in various industry products. Common issues encountered when designing this type of systems are nonlinearities and uncertainties (e.g., unknown parameters, unmodeled dynamics, and disturbances). In this paper, we study controller design for a class of motion systems with rotary components. The systems are assumed to have unknown parameters which...
In most batch processes, quality control measurements cannot be completed before the next batch operation. Thus, the corrective step is often delayed by one batch or more. The uncertain duration of delay with stochastic characteristics can be treated as a random variable of unknown distribution. Coupled with inaccurate process models, the delay may lead to significant process output variations even...
In this paper, a new robust Iterative Learning Control (ILC) algorithm has been proposed for linear systems in the presence of iteration-varying parametric uncertainties. The robust ILC design is formulated as a min-max problem using a quadratic performance criterion subject to constraints of the control input update. An upper bound of the maximization problem is derived, then, the solution of the...
In this paper, interconnected iterative learning control loops are used to drive the output of general multi-input-multi-output nonlinear systems with general input uncertainties to the desired output. New convergence conditions are obtained to ensure the convergence of the overall system. A simulation example shows the effectiveness of the proposed method.
This paper is concerned with the simultaneous design of plant structure parameters (passive components) and controllers (active components) in order to achieve the optimal system performance. With LFT (linear fractional transformation) formulation, the simultaneous design problem can be transferred into a design problem of a controller with specific construction. It is a complex control problem with...
This paper proposes a new blind approach to identification of Hammerstein-Wiener models, where a linear dynamics is embedded between two static nonlinearities. The blind approach directly aims at estimating immeasurable inner input and output, with noise effects in consideration. By exploiting input's piece-wise constant property, the parameters of the inverse output nonlinearity and the denominator...
A fundamental problem in systems biology consists of determining the equilibrium points of genetic regulatory networks, since the knowledge of these points is often required in order to investigate important properties such as stability. Unfortunately, this problem amounts to computing the solutions of a system of nonlinear equations, and it is well known that this is a difficult problem as no existing...
Due to the large economic and environmental impact and pervasive application, engine maintenance policy optimization has attracted the research interest in the past several decades. Markov decision process (MDP) provides a general framework for this problem, but the large state space makes it difficult to apply the traditional value iteration and policy iteration in practice. How to approximate the...
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