Quadratic control of stochastic hybrid systems with renewal transitions

We study the quadratic control of a class of stochastic hybrid systems with linear continuous dynamics for which the lengths of time that the system stays in each mode are independent random variables with given probability distribution functions. We derive a condition for finding the optimal feedback policy that minimizes a discounted infinite horizon cost. We show that the optimal cost is the solution to a set of differential equations with unknown boundary conditions. Furthermore, we provide a recursive algorithm for computing the optimal cost and the optimal feedback policy. The applicability of our result is illustrated through a numerical example, motivated by stochastic gene regulation in biology.     

Benchmarking Fluvial Dynamics for Process‐Based River Restoration: the Upper Rhine River (1816–2014)

Multi‐temporal analysis of river‐floodplain processes is a key tool for the identification of reference conditions or benchmarks and for the evaluation of deviations or deficits as a basis for process‐based river restoration in large modified rivers. This study developed a methodology for benchmarking fluvial processes at river segment level, focusing on those interrelations between morphodynamics (aggradation, erosion, channel shift) and vegetation succession (initial, colonization, transition) that condition habitat structure. Habitat maps of the free‐flowing Upper Rhine River downstream from Iffezheim dam (France–Germany border) were intersected with a geographic information system‐based approach. Patches showing trajectories of anthropization, changeless, progression and regression allowed for the identification of natural and human‐induced processes over almost 200 years. Before channelization, the riverine system was characterized by a shifting habitat mosaic with natural heterogeneity, high degree of surface water connectivity and equilibrium between progression and regression processes. On the other hand, the following 175 years of human interventions led to severe biogeomorphologic deficits evidenced by loss of natural processes and habitat heterogeneity, hydrological disconnection between the river and its floodplain and imbalance of progression versus regression dynamics. The main driving forces of change are found in hydromorphological impacts (channelization, regulation and hydropower plant construction). Regression processes are now almost absent and have to be the objective of process‐based river restoration measures for the studied river‐floodplain system. A sustainable view on water management and river restoration should aim at a more resilient riverine system by balancing the recovery of natural processes with societal needs. Copyright © 2016 John Wiley & Sons, Ltd.     

On the filtered Smith predictor for MIMO processes with multiple time delays

This paper discusses about a unified implementation structure of the filtered Smith predictor (FSP) for MIMO processes with multiple time delays. Two kinds of dead-time free models are analyzed in order to extend the original properties of the SISO Smith predictor to MIMO processes with multiple time delays. It is demonstrated that FSP strategy can be applied to control open-loop unstable processes with multiple time delays by considering a model without any input, output or internal coupling delays. Moreover, for open-loop stable processes, it is shown that the FSP scheme can be used to speed-up disturbance rejection of processes with multiple time delays by using a nominal model without delay. Different simulation examples are used to illustrate the proposed strategy properties and advantages over other MIMO time-delay compensators. The results may be considered to control either square or non-square processes.     

L2 disturbance attenuation for highly dissipative nonlinear spatially distributed processes via HJI approach

For many practical industrial spatially distributed processes (SDPs), their dynamics are usually described by highly dissipative nonlinear partial differential equations (PDEs). In this paper, we address the L₂ disturbance attenuation problem of nonlinear SDPs using the Hamilton–Jacobi–Isaacs (HJI) approach. Firstly, by collecting an ensemble of PDE states, Karhunen–Loève decomposition (KLD) is employed to compute empirical eigenfunctions (EEFs) of the SDP based on the method of snapshots. Subsequently, these EEFs together with singular perturbation (SP) technique are used to obtain a finite-dimensional slow subsystem of ordinary differential equation (ODE) that accurately describes the dominant dynamics of the PDE system. Secondly, based on the slow subsystem, the L₂ disturbance attenuation problem is reformulated and a finite-dimensional H_∞ controller is synthesized in terms of the HJI equation. Moreover, the stability and L₂-gain performance of the closed-loop PDE system are analyzed. Thirdly, since the HJI equation is a nonlinear PDE that has proven to be impossible to solve analytically, we combine the method of weighted residuals (MWR) and simultaneous policy update algorithm (SPUA) to obtain its approximate solution. Finally, the simulation studies are conducted on a nonlinear diffusion-reaction process and a temperature cooling fin of high-speed aerospace vehicle, and the achieved results demonstrate the effectiveness of the developed control method.     

State space model predictive fault-tolerant control for batch processes with partial actuator failure

This paper presents a state space model predictive fault-tolerant control scheme for batch processes with unknown disturbances and partial actuator faults. To develop the model predictive fault-tolerant control, the batch process is first treated into a non-minimal representation using state space transformation. The relevant concepts of the corresponding model predictive fault-tolerant control is thus introduced through state space formulation, where improved closed-loop control performance is achieved even with unknown disturbances and actuator faults, because, unlike traditional model predictive fault-tolerant control, the proposed control method can directly regulate the process output/input changes in the design. For performance comparison, a traditional model predictive fault-tolerant control is also designed. Application to injection velocity control shows that the proposed scheme achieve the design objective well with performance improvement.     

Size segregation in gas-solid fluidized beds with continuous size distributions

Discrete-particle simulations of a gas-solid fluidized bed are used to investigate the species segregation (de-mixing) behavior of systems with continuous particle size distributions. Both Gaussian and lognormal distributions are investigated over a range of distribution widths, restitution and friction coefficients, and gas velocities. The results indicate that: (i) the average particle diameter decreases as the height within the bed increases, (ii) the level of segregation increases with an increase in the width of the particle size distribution, and (iii) segregation is attenuated as bubbling becomes more vigorous. Furthermore, the shape of the local size distribution (i.e., Gaussian or lognormal) is found to mimic that of the overall size distribution in most regions of the fluidized bed.     

Texaco与Shell煤气化工艺比较分析

煤气化技术对于促进煤炭的综合利用、改善当前资源紧缺状况,并减少环境污染具有重要的意义。阐述了Texaco和Shell煤气化的工艺流程,并对2种煤气化工艺进行了比较分析,找出各自的优缺点,为煤气化工艺的选择提供参考。     

基于动态MANCOVA的混合制程虚拟测量算法

在晶圆/液晶面板等批次加工过程中,产品质量的及时估计与品质管制是提高产能和降低成本的有效途径.针对"少量多样"的混合制程,利用逐步回归算法挑选该制程的关毽变量,引入产品的效益因子,建立混合制程的虚拟测量模型;为克服系统扰动对模型精度的影响,以产品效益因子为状态量建立该制程的状态方程,利用Kalman滤波器递归估计模型参数得到动态的MANCOVA模型;最后通过某湿式蚀刻制程的工程应用验证了该算法的有效性.     

秦安县农村户用改进型沼气池建造的关键技术

近年来,随着我县农村户用沼气建设力度的不断加大,为缓解我县能源资源短缺的现状,通过对农村户用沼气池施工技术及工艺的改进,进行技术集成示范,总结出秦安农村户用改进型沼气池的建造技术,为该地区沼气事业的发展提供科学依据.