Displaying similar documents to “Systems with associative dynamics”

Nonlinear system identification using heterogeneous multiple models

Rodolfo Orjuela, Benoît Marx, José Ragot, Didier Maquin (2013)

International Journal of Applied Mathematics and Computer Science

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Multiple models are recognised by their abilities to accurately describe nonlinear dynamic behaviours of a wide variety of nonlinear systems with a tractable model in control engineering problems. Multiple models are built by the interpolation of a set of submodels according to a particular aggregation mechanism, with the heterogeneous multiple model being of particular interest. This multiple model is characterized by the use of heterogeneous submodels in the sense that their state...

Efficient nonlinear predictive control based on structured neural models

Maciej Ławryńczuk (2009)

International Journal of Applied Mathematics and Computer Science

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This paper describes structured neural models and a computationally efficient (suboptimal) nonlinear Model Predictive Control (MPC) algorithm based on such models. The structured neural model has the ability to make future predictions of the process without being used recursively. Thanks to the nature of the model, the prediction error is not propagated. This is particularly important in the case of noise and underparameterisation. Structured models have much better long-range prediction...

Recursive identification algorithm for dynamic systems with output backlash and its convergence

Ruili Dong, Qingyuan Tan, Yonghong Tan (2009)

International Journal of Applied Mathematics and Computer Science

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This paper proposes a recursive identification method for systems with output backlash that can be described by a pseudoWiener model. In this method, a novel description of the nonlinear part of the system, i.e., backlash, is developed. In this case, the nonlinear system is decomposed into a piecewise linearized model. Then, a modified recursive general identification algorithm (MRGIA) is employed to estimate the parameters of the proposed model. Furthermore, the convergence of the MRGIA...

Self-tuning controllers based on orthonormal functions

Jozef Hejdiš, Štefan Kozák, Ľubica Juráčková (2000)

Kybernetika

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Problems of the system identification using orthonormal functions are discussed and algorithms of computing parameters of the discrete time state- space model of the plant based on the generalized orthonormal functions and the Laguerre functions are derived. The adaptive LQ regulator and the predictive controller based on the Laguerre function model are also presented. The stability and the robustness of the closed loop using the predictive controller are investigated.