Bilateral boundary control of an input delayed 2-D reaction-diffusion equation

In this paper, a delay compensation design method based on PDE backstepping is developed for a two-dimensional reaction-diffusion partial differential equation (PDE) with bilateral input delays. The PDE is defined in a rectangular domain, and the bilateral control is imposed on a pair of opposite sides of the rectangle. To represent the delayed bilateral inputs, we introduce two 2-D transport PDEs that form a cascade system with the original PDE. A novel set of backstepping transformations is proposed for delay compensator design, including one Volterra integral transformation and two affine Volterra integral transformations. Unlike the kernel equation for 1-D PDE systems with delayed boundary input, the resulting kernel equations for the 2-D system have singular initial conditions governed by the Dirac Delta function. Consequently, the kernel solutions are written as a double trigonometric series with singularities. To address the challenge of stability analysis posed by the singularities, we prove a set of inequalities by using the Cauchy-Schwarz inequality, the 2-D Fourier series, and the Parseval's theorem. A numerical simulation illustrates the effectiveness of the proposed delay-compensation method.Comment: 11 pages, 3 figures(including 8 sub-figures

Gain Scheduling with a Neural Operator for a Transport PDE with Nonlinear Recirculation

To stabilize PDE models, control laws require space-dependent functional gains mapped by nonlinear operators from the PDE functional coefficients. When a PDE is nonlinear and its "pseudo-coefficient" functions are state-dependent, a gain-scheduling (GS) nonlinear design is the simplest approach to the design of nonlinear feedback. The GS version of PDE backstepping employs gains obtained by solving a PDE at each value of the state. Performing such PDE computations in real time may be prohibitive. The recently introduced neural operators (NO) can be trained to produce the gain functions, rapidly in real time, for each state value, without requiring a PDE solution. In this paper we introduce NOs for GS-PDE backstepping. GS controllers act on the premise that the state change is slow and, as a result, guarantee only local stability, even for ODEs. We establish local stabilization of hyperbolic PDEs with nonlinear recirculation using both a "full-kernel" approach and the "gain-only" approach to gain operator approximation. Numerical simulations illustrate stabilization and demonstrate speedup by three orders of magnitude over traditional PDE gain-scheduling. Code (Github) for the numerical implementation is published to enable exploration.Comment: 16 pages, 5 figure

Nonlinear bilateral output-feedback control for a class of viscous Hamilton¿Jacobi PDEs

We tackle the boundary control and estimation problems for a class of viscous Hamilton–Jacobi PDEs, considering bilateral actuation and sensing, i.e., at the two boundaries of a 1-D spatial domain. We first solve the nonlinear trajectory generation problem for this type of PDEs, providing the necessary feedforward actions at both boundaries. We then design an observer-based output-feedback control law, which consists of two main elements—a nonlinear observer that is constructed utilizing measurements from both boundaries and state-feedback laws, which are employed at the two boundary ends. All of our designs are explicit since they are constructed interlacing a feedback linearizing transformation with backstepping. Due to the fact that the linearizing transformation is locally invertible, only a regional stability result is established, combining this transformation with backstepping, suitably formulated to handle the case of bilateral actuation and sensing. We illustrate the developed methodologies via application to traffic flow control and we present consistent simulation results

Nonlinear bilateral output-feedback control for a class of viscous Hamilton–Jacobi PDEs

Nikolaos Bekiaris-Liberis was supported by the funding from the European Commission’s Horizon 2020 research and innovation programme under the Marie Sklodowska- Curie Grant Agreement No. 747898, project PADECOT. Rafael Vazquez acknowledges financial support of the Spanish Ministerio de Economia y Competitividad under grant MTM2015-65608-P.Summarization: We tackle the boundary control and estimation problems for a class of viscous Hamilton–Jacobi PDEs, considering bilateral actuation and sensing, i.e., at the two boundaries of a 1-D spatial domain. We first solve the nonlinear trajectory generation problem for this type of PDEs, providing the necessary feedforward actions at both boundaries. We then design an observer-based output-feedback control law, which consists of two main elements—a nonlinear observer that is constructed utilizing measurements from both boundaries and state-feedback laws, which are employed at the two boundary ends. All of our designs are explicit since they are constructed interlacing a feedback linearizing transformation with backstepping. Due to the fact that the linearizing transformation is locally invertible, only a regional stability result is established, combining this transformation with backstepping, suitably formulated to handle the case of bilateral actuation and sensing. We illustrate the developed methodologies via application to traffic flow control and we present consistent simulation results.Presented on: Automatic