Control of 1-D parabolic PDEs with Volterra nonlinearities, Part I: Design

  • Authors:
  • Rafael Vazquez;Miroslav Krstic

  • Affiliations:
  • Departamento de Ingeniería Aeroespacial, Universidad de Sevilla, 41092 Seville, Spain;Department of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, CA 92093-0411, United States

  • Venue:
  • Automatica (Journal of IFAC)
  • Year:
  • 2008

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Abstract

Boundary control of nonlinear parabolic PDEs is an open problem with applications that include fluids, thermal, chemically-reacting, and plasma systems. In this paper we present stabilizing control designs for a broad class of nonlinear parabolic PDEs in 1-D. Our approach is a direct infinite dimensional extension of the finite-dimensional feedback linearization/backstepping approaches and employs spatial Volterra series nonlinear operators both in the transformation to a stable linear PDE and in the feedback law. The control law design consists of solving a recursive sequence of linear hyperbolic PDEs for the gain kernels of the spatial Volterra nonlinear control operator. These PDEs evolve on domains T"n of increasing dimensions n+1 and with a domain shape in the form of a ''hyper-pyramid'', 0@?@x"n@?@x"n"-"1...@?@x"1@?x@?1. We illustrate our design method with several examples. One of the examples is analytical, while in the remaining two examples the controller is numerically approximated. For all the examples we include simulations, showing blow up in open loop, and stabilization for large initial conditions in closed loop. In a companion paper we give a theoretical study of the properties of the transformation, showing global convergence of the transformation and of the control law nonlinear Volterra operators, and explicitly constructing the inverse of the feedback linearizing Volterra transformation; this, in turn, allows us to prove L^2 and H^1 local exponential stability (with an estimate of the region of attraction where possible) and explicitly construct the exponentially decaying closed loop solutions.