In this paper, a model predictive controller is developed for controlling the main primary circuit dynamics of pressurized water nuclear power plants during load-change transients. The hybrid model of the plant is suc...
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This paper proposes a simple robust model predictive algorithm for discrete time linear parameter varying uncertain systems, which depend nonlinearly on their parameters. The method was derived from the robust MPC alg...
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In the paper the road holding of a heavy vehicle is improved by using unilateral braking. The goal of the control design is to reduce the effect of the lateral acceleration of the vehicle, when it exceeds a predefined...
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The idea of inversion-based direct input reconstruction for robust detection and separation of multiple, possibly simultaneous faults in the presence of external, non-mutually separable disturbances for linear dynamic...
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This paper presents an approach towards learning enhanced motion control of DC motor, suitable for applications involving repeated iterations of motion trajectories. The overall structure of the control consists of a ...
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ISBN:
(纸本)8986510081
This paper presents an approach towards learning enhanced motion control of DC motor, suitable for applications involving repeated iterations of motion trajectories. The overall structure of the control consists of a feedback and a feed-forward components. The model-free learning adaptive feedback control (MFLAC) provides for the main system stabilization and an iterative learning control (ILC) algorithm is proposed to serve as a feedforward compensation to nonlinear and unknown dynamics and disturbances, thereby enhancing the improvement achievable with PID or MFLAC alone. It serves as the basis for simulation study of the proposed control scheme. A comparison of the performance achieved with traditional PID and MFLAC is also provided to highlight the advantages of the additional intelligent feedforward mode.
In this paper, an Extended Kalman-Bucy-Filter approach for fault detection and diagnosis of an hydraulic servo-axis is presented. The filter improves the results with the EKF as reported in literature since it uses a ...
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In this paper, an Extended Kalman-Bucy-Filter approach for fault detection and diagnosis of an hydraulic servo-axis is presented. The filter improves the results with the EKF as reported in literature since it uses a new model structure, considers nonlinear valve spool displacement-flow relationships and incorporates temperature effects. The performance of the newly proposed architecture is evaluated thoroughly at a testbed in the presence of both process faults and sensor faults. For sensor faults, the smallest reliably detectable sensor fault is determined. The method is finally compared to parity equations and parameter estimation, which have also successfully been applied to the supervision oif hydraulic servo axes.
This paper addresses the state feedback H∞ control for a class of nonlinear system based on its L2 gain computation, where the technique of the sum of squares decomposition is applied. By reformulating the Hamilton-J...
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The Tensor Product model transformation is a numerical method that is capable of uniformly transforming LPV (linear parameter-varying) dynamic models into polytopic forms, both in a theoretical and algorithmic context...
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The Tensor Product model transformation is a numerical method that is capable of uniformly transforming LPV (linear parameter-varying) dynamic models into polytopic forms, both in a theoretical and algorithmic context. Using the TP model transformation, different optimization and convexity constraints can be considered, and transformations can be executed without any analytical interactions, within a reasonable amount of time (irrespective of whether the model is given in the form of analytical equations resulting from physical considerations, as an outcome of soft computing based identification techniques such as neural networks or fuzzy logic based methods, or as a result of a blackbox identification). Thus, the transformation replaces the usual analytical and oftentimes complex conversions with a numerically tractable and straightforward series of operations. The TP model transformation generates two kinds of polytopic models. Firstly, it numerically reconstructs the HOSVD (Higher Order Singular Value) based canonical form of LPV models. This is a new and unique polytopic representation. This form extracts the unique structure and various important properties of a given LPV model in the same sense as the HOSVD does for matrices and tensors. Secondly, the TP model transformation generates various convex polytopic forms, upon which LMI (Linear Matrix Inequality) based multi-objective control design techniques can immediately be executed in order to satisfy the given control performance requirements. TP tool is a MATLAB Toolbox that implements the Tensor Product Model Transformation based control Design framework. It is available at http://***.
This paper proposes a general Kernel-Bayesian framework for object tracking. In this framework, the kernel based method-mean shift algorithm is embedded into the Bayesian framework seamlessly to provide a heuristic pr...
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作者：
Edelmayer, A.Miranda, M.Systems and Control Laboratory
Computer and Automation Research Institute Hungarian Academy of Sciences Kende u. 13-17 Budapest H-1111 Hungary
Faculty of Engineering Department of Chemical Engineering Mérida Venezuela
This paper discusses the application of the idea of federated filtering to the estimation of intrinsically nonlinear distributed systems by examining its impacts on filtering performance by using the Extended Kalman F...
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