Optimal Control of Terminal Processes Using Neural Networks  

Oleh:

Plumer, E. S.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 7 no. 2 (1996), page 408-418.
Topik: neural network; optimal control; terminal processes; neural networks

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.1 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Feedforward neural networks are capable of approximating continuous multivariate functions and, as such, can implement nonlinear state - feedback controllers. Training methods such as backpropagation - through - time (BPTT), however, do not deal with terminal control problems in which the specified cost function includes the elapsed trajectory - time. In this paper, an extension to BPTT is proposed which addresses this limitation. The controller design is reformulated as a constrained optimization problem defined over the entire field of extremals and in which the set of trajectory times is incorporated into the cost function. Necessary first - order stationary conditions are derived which correspond to standard BPTT with the addition of certain transversality conditions. The new gradient algorithm based on these conditions, called time - optimal backpropagation through time, is tested on two benchmark minimum - time control problems.

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