Optimization-Based Stabilization of Sampled-Data Nonlinear Systems via Their Approximate Discrete-Time Models


We present results on numerical regulator design for sampled-data nonlinear plants via their approximate discrete-time plant models. The regulator design is based on an approximate discrete-time plant model and is carried out either via an infinite horizon optimization problem or via a finite horizon with terminal cost optimization problem. In both cases, we discuss situations when the sampling period T and the integration period h used in obtaining the approximate discrete-time plant model are the same or they are independent of each other. We show that, using this approach, practical and/or semiglobal stability of the exact discrete-time model is achieved under appropriate conditions.

MSC codes

  1. 93D15
  2. 49N35
  3. 65P40


  1. controller design
  2. asymptotic controllability
  3. stabilization
  4. numerical methods
  5. optimal control

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Information & Authors


Published In

cover image SIAM Journal on Control and Optimization
SIAM Journal on Control and Optimization
Pages: 98 - 122
ISSN (online): 1095-7138


Published online: 26 July 2006

MSC codes

  1. 93D15
  2. 49N35
  3. 65P40


  1. controller design
  2. asymptotic controllability
  3. stabilization
  4. numerical methods
  5. optimal control



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