Implicit function based adaptive control of non-canonical form discrete-time nonlinear systems
| Autor: | Ji-Feng Zhang, Xiao-Kang Liu, Yanjun Zhang |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Adaptive control Implicit function Computer science 020208 electrical & electronic engineering Parameterized complexity 02 engineering and technology Stability (probability) Nonlinear system 020901 industrial engineering & automation Control and Systems Engineering Control theory Bounded function 0202 electrical engineering electronic engineering information engineering Feedback linearization Electrical and Electronic Engineering Parametric statistics |
| Zdroj: | Automatica. 129:109629 |
| ISSN: | 0005-1098 |
| Popis: | This paper presents a new study on adaptive state feedback output tracking control problem for uncertain discrete-time nonlinear systems in a general non-canonical form. Time-advance operations on the output of such systems result in the output dynamics being nonlinearly dependent on the control input and unknown parameters, which leads to three technical issues: implicit relative degree; nonlinearly parameterized uncertainties; and non-affine control input. To address these issues, this paper first employs feedback linearization and implicit function theory to construct a relative degree dependent normal form; then proposes an adaptive parametric reconstruction based method to simultaneously deal with linearly and nonlinearly parameterized uncertainties in the output dynamics; and finally constructs a key implicit function equation to derive a unique adaptive control law which ensures closed-loop stability and asymptotic output tracking. An explicitly iterative solution based adaptive control law is also proposed to ensure closed-loop stability and bounded output tracking within any degree of accuracy. The simulation verifies the effectiveness of the proposed adaptive control method. |
| Databáze: | OpenAIRE |
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