Original contributionFeedback-error-learning neural network for trajectory control of a robotic manipulator
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2022, Neural NetworksCitation Excerpt :As will be shown later, estimating a form of these values will directly produce error corrections, and adjust the control structure of the system. In contrast, approaches using internal models of the system being controlled (called the plant) need to train such models, and make them produce corrections; this usually requires a pre-existing control structure (e.g. Miyamoto, Kawato, Setoyama, & Suzuki, 1988; Porrill, Dean, & Stone, 2004), or a form of error backpropagation (Jordan & Rumelhart, 1992). In addition of not depending on a forward model, the model we present consists entirely of neurons.
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Present address: Sumitomo electric industries, Ltd., Osaka 554, Japan.
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Present address: ATR Auditory and Visual Perception Research Laboratories, Osaka 540, Japan.