Distributed Consensus Observers-Based H∞ Control of Dissipative PDE Systems Using Sensor Networks

1  Abstract—This paper considers the problem of finite dimensional output feedback H  control for a class of nonlinear spatially distributed processes (SDPs) described by highly dissipative partial differential equations (PDEs), whose state is observed by a sensor network (SN) with a given topology. A highly dissipative PDE system typically involves a spatial differential operator with eigenspectrum that can be partitioned into a finite-dimensional slow one and an infinite-dimensional stable fast complement. Motivated by this fact, the modal decomposition and singular perturbation techniques are initially applied to the PDE system to derive a finite dimensional ordinary differential equation model, which accurately captures the dynamics of the slow modes of the PDE system. Subsequently, based on the slow system and the topology of the SN, a set of finite dimensional distributed consensus observers are constructed to estimate the state of the slow system. Then, a centralized control scheme, which only uses the available estimates from a specified group of SN nodes, is proposed for the PDE system. An H  control design method is developed in terms of bilinear matrix inequality (BMI), such that the original closed-loop PDE system is exponentially stable and a prescribed level of disturbance attenuation is satisfied for the slow system. Furthermore, a suboptimal H  controller is also provided to make the attenuation level as small as possible, which can be obtained via a local optimization algorithm that treats the BMI as double linear matrix inequality. Finally, the proposed method is applied to the control of one dimensional Kuramoto-Sivashinsky equation (KSE) system.