A Novel Adaptive Control Algorithm based on Nonlinear Laguerre-Volterra Observer
Zhang H.T.
Transactions of the Institute of Measurement and Control, 2007
To appear
Abstract
By expanding each kernels using orthonormal Laguerre series, a Volterra functional series is used to represent the input-output relation of a nonlinear dynamic system. When Volterra series and Laguerre series truncations are allowed, an appropriate choice of the Laguerre filter pole permits a description of the process dynamics with a small number of parameters. Feeding back the error of the outputs of the plant and the model, we design a novel nonlinear state observer, based on which a stable output feedback control law is derived for both regulator and tracking problems. To support this algorithm, we present the theoretical analyses of its nominal stability, which allows obtaining the state feedback gain and the observer gain solely by solving two LMIs (linear matrix inequalities). In addition, another theorem is also given to show its capability of minimizing the steady-state tracking errors. For handling more complex dynamics, we improve the standard RLSE (recursive least square estimation) identification method to a normalized one with guaranteed convergence. Finally, control simulations on a benchmark problem-CSTR (continuous stirring tank reactor) process and experiments on a chemical reactor temperature control system are performed. This method, especially its essential idea of Volterra nonlinear observer, has shown the great potential for the control of a large class of nonlinear dynamic systems.
BibTex Entry
- @Article{,
- author = {Zhang H.T.},
- journal = {Transactions of the Institute of Measurement and Control},
- title = {A Novel Adaptive Control Algorithm based on Nonlinear Laguerre-Volterra Observer},
- year = {2007},
- note = {To appear}
- }
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