Competitive learning algorithms for vector quantization
Neural Networks
Properties of generalized predictive control
Automatica (Journal of IFAC) - Identification and systems parameter estimation
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This paper describes a robust controller using difference signals and multiple competitive associative nets (CAN2s) and flexibly applicable to different control specifications or objectives. Using difference signals of a plant to be controlled, the CAN2 is capable of leaning piecewise Jacobian matrices of nonlinear dynamics of the plant as well as the control objective. By means of employing the GPC (generalized predictive controller), a robust control method to switch multiple CAN2s to cope with plant parameter change is introduced. We show the effectiveness of the present method via numerical experiments of a crane system.