Boundary control design of a class of time fractional‐order nonlinear reaction–diffusion systems (FNRDSs) is considered in three cases: domain‐averaged measurement, collocated boundary point measurement, and anti‐collocated boundary point measurement. For domain‐averaged measurement and collocated boundary point measurement, boundary controllers are designed directly based on the measurements, respectively. For the anti‐collocated boundary point measurement, to overcome the difficulty that the measurement cannot be used for the controller design directly, an observer is constructed firstly, and then, an observer‐based boundary controller is designed. Sufficient conditions for Mittag–Leffler (M‐L) stability of the closed‐loop system are all provided in terms of linear matrix inequalities (LMIs). Numerical simulation results are provided to illustrate the feasibility and effectiveness of the proposed methods.
This paper studies the problem of adaptive neural networks control (ANNC) for uncertain parabolic distributed parameter systems (DPSs) with nonlinear periodic time-varying parameter (NPTVP). Firstly, the uncertain nonlinear dynamic and unknown periodic TVP are represented by using neural networks (NNs) and Fourier series expansion (FSE), respectively. Secondly, based on the ANNC and reparameterization approaches, two control algorithms are designed to make the uncertain parabolic DPSs with NPTVP asymptotically stable. The sufficient conditions of the asymptotically stable for the resulting closed-loop systems are also derived. Finally, a simulation is carried out to verify the effectiveness of the two control algorithms designed in this work.
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