This paper is focused on the state estimation problem for nonlinear systems with unknown statistics of measurement *** on the cubature Kalman filter,we propose a new nonlinear filtering algorithm that employs a skew t...
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This paper is focused on the state estimation problem for nonlinear systems with unknown statistics of measurement *** on the cubature Kalman filter,we propose a new nonlinear filtering algorithm that employs a skew t distribution to characterize the asymmetry of the measurement *** system states and the statistics of skew t noise distribution,including the shape matrix,the scale matrix,and the degree of freedom(DOF)are estimated jointly by employing variational Bayesian(VB)*** proposed method is validated in a target tracking *** of the simulation indicate that the proposed nonlinear filter can perform satisfactorily in the presence of unknown statistics of measurement noise and outperform than the existing state-of-the-art nonlinear filters.
This paper studies global synchronization between a heterogeneous dynamical network and a known target trajectory via distributed impulsive control. Synchronization with an error level, called quasi-synchronization, i...
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This paper deals with the H ∞ filter design problem for event-triggered networked control systems (NCSs), where the next task release time and finishing time are predicted based on the sampled states. The closed-loo...
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This paper deals with the H ∞ filter design problem for event-triggered networked control systems (NCSs), where the next task release time and finishing time are predicted based on the sampled states. The closed-loop filtering error system is modeled as a linear system with an interval time-varying delay and event-triggered communication strategy. Based on this model, some novel criteria for the asymptotic stability analysis and H ∞ filter design of the event-triggered NCSs with time-varying delay are established to guarantee a prescribed H ∞ disturbance rejection attenuation level. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method.
For a class of nonlinear discrete time system with fast time-varying or jumping parameters, a multiple models adaptive controller (MMAC) based on cluster-optimization is proposed. Based on the input-output data, the s...
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The p-xylene (PX) oxidation process is of great industrial importance because of the strong demand of the global polyester fiber. A steady-state model of the PX oxidation has been studied by many researchers. In our p...
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A double-layer optimization algorithm (DLOA) was proposed to solve the minimum time dynamic optimization problem. The first step of DLOA was to discrete time region and control region. The inner optimization is to con...
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A double-layer optimization algorithm (DLOA) was proposed to solve the minimum time dynamic optimization problem. The first step of DLOA was to discrete time region and control region. The inner optimization is to construct optimal control problem with free final states. Differential evolution algorithm is used to find the optimal solution in given terminal time, then the optimization results was compared with the threshold set. In the outer, DLOA calculated the time range of next iteration according to the inner calculation. When applied to typical minimum time dynamic optimization problem, DLOA demonstrated a competitive optimal searching ability and more accurate optimization results. DLOA could solve the optimization problem with local optimum and applied to models without gradient information.
Modern chemicalprocesses are usually characterized by large-scale,complex correlation,and strong dynamics,and monitoring of such processes is *** paper proposes a performance-driven fault-relevant dynamic principal c...
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ISBN:
(纸本)9781538629185
Modern chemicalprocesses are usually characterized by large-scale,complex correlation,and strong dynamics,and monitoring of such processes is *** paper proposes a performance-driven fault-relevant dynamic principal component(FRDPC) subspace construction integrated with Bayesian inference method to achieve efficient monitoring for dynamic chemical ***,dynamic principal component analysis is employed to deal with both auto-correlation and cross-correlation among ***,considering fault information has no definite mapping to a certain dynamic principal component(DPC) and the existence of non-beneficial DPCs may cause redundancy in the monitoring,an FRDPC subspace is constructed for each fault through the performance-driven DPC *** new process measurements are examined in each FRDPC subspace as well as the residual *** monitoring results in all subspaces are fused to a comprehensive index through Bayesian inference to provide an intuitive indication of the process *** studies on a numerical example and the Tennessee Eastman benchmark process indicate the efficiency.
This paper proposes a framework for solving high-dimensional robust multi-objective optimization problems. A decision variable classification-based framework is developed to search for robust Pareto-optimal solutions....
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In a resource limited multi-agent system, it is of practical importance to select a fraction of nodes (agents) to provide control inputs such that consensus can be achieved with optimized performance in terms of netwo...
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Brain computer interface (BCI) could help patients to manipulate external devices based on the specific brain activities. One of the most popular BCI systems is the visual-based BCI system. Mostly, users were asked to...
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ISBN:
(纸本)9781467376808
Brain computer interface (BCI) could help patients to manipulate external devices based on the specific brain activities. One of the most popular BCI systems is the visual-based BCI system. Mostly, users were asked to pay attention not only to the target stimulus, but also to the real control target which would bring high workload to users and affect the control efficiency of BCI systems. In this paper, a real-time monitoring system was developed to solve this problem by showing the environment information from the camera on the computer screen. Five subjects took part in this experiment and all of them were asked to control a small car to the target position. Our result showed that all subjects could finish the task within two or three minutes. In this study, subject did not need to switch their attention on the car which was out of their sight, and it would help to improve the usability of BCI in the practical application.
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