Feedback control of oscillations in combustion and cavity flows

This thesis considers the control of combustion oscillations, motivated by the susceptibility of lean premixed combustion to such oscillations, and the long and expensive development and commissioning times that this is giving rise to. The controller used is both closed-loop, employing an actuator to modify some system parameter in response to a measured signal, and adaptive, meaning that it is able to maintain control over a wide range of operating conditions. The controller is applied to combustion systems with annular geometries, where instabilities can occur both longitudinally and azimuthally, and which require multiple sensors and multiple actuators for control. One of the requirements of Lyapunov-based adaptive control which is particularly troublesome for combustion systems is then addressed: that the sign of the high-frequency gain of the open-loop system is known. We address it by using an adaptive controller which employs a Nussbaum gain, and successfully apply it experimentally to combustion oscillations in a Rijke tube. Another type of fluid-acoustic resonance is then considered: the compressible flow past a shallow cavity. We start by finding a linear model of the cavity flow's dynamics, or its `transfer function', which we identify from direct numerical simulations. We compare this measured transfer function to that given by a conceptual model which is based on the Rossiter mechanism, and which models each component of the flow physics separately. We then look at using closed-loop control to eliminate these cavity oscillations. We start by designing a robust $\mathcal{H}_2$ controller based on a balanced reduced order model of the system, the model being provided by the Eigensystem Realization Algorithm (ERA). The robust controller provides closed-loop stability over a much wider Mach number range than seen in previous studies. Finally, we look at the suitability of the adaptive controller, earlier developed for combustion oscillations, for the cavity. Based on some general properties of the cavity flow, and by using collocated control, the oscillations are eliminated at all Mach numbers tested in the range $0.4 \le M \le 0.8$.This work was supported by the EPSRC and Rolls-Royce plc

Combined MIMO adaptive and decentralized controllers for broadband active noise and vibration control

Recent implementations of multiple-input multiple-output adaptive controllers for reduction of broadband noise and vibrations provide considerably improved performance over traditional adaptive algorithms. The most significant performance improvements are in terms of speed of convergence, the \ud amount of reduction, and stability of the algorithm. Nevertheless, if the error in the model of the relevant transfer functions becomes too large then the system may become unstable or lose performance. On-line adaptation of the model is possible in principle but, for rapid changes in the model, necessitates \ud a large amount of additional noise to be injected in the system. It has been known for decades that a combination of high-authority control (HAC) and low-authority control (LAC) could lead to improvements with respect to parametric uncertainties and unmodeled dynamics. In this paper a full digital implementation of such a control system is presented in which the HAC (adaptive MIMO control) is implemented on a CPU and in which the LAC (decentralized control) is implemented on a high-speed Field Programmable Gate Array. Experimental results are given in which it is demonstrated that the HAC/LAC combination leads to performance advantages in terms of stabilization under parametric uncertainties and reduction of the error signal

Fuzzy-logic-based control, filtering, and fault detection for networked systems: A Survey

This paper is concerned with the overview of the recent progress in fuzzy-logic-based filtering, control, and fault detection problems. First, the network technologies are introduced, the networked control systems are categorized from the aspects of fieldbuses and industrial Ethernets, the necessity of utilizing the fuzzy logic is justified, and the network-induced phenomena are discussed. Then, the fuzzy logic control strategies are reviewed in great detail. Special attention is given to the thorough examination on the latest results for fuzzy PID control, fuzzy adaptive control, and fuzzy tracking control problems. Furthermore, recent advances on the fuzzy-logic-based filtering and fault detection problems are reviewed. Finally, conclusions are given and some possible future research directions are pointed out, for example, topics on two-dimensional networked systems, wireless networked control systems, Quality-of-Service (QoS) of networked systems, and fuzzy access control in open networked systems.This work was supported in part by the National Natural Science Foundation of China under Grants 61329301, 61374039, 61473163, and 61374127, the Hujiang Foundation of China under Grants C14002 andD15009, the Engineering and Physical Sciences Research Council (EPSRC) of the UK, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany

Analysis, filtering, and control for Takagi-Sugeno fuzzy models in networked systems

Copyright © 2015 Sunjie Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.The fuzzy logic theory has been proven to be effective in dealing with various nonlinear systems and has a great success in industry applications. Among different kinds of models for fuzzy systems, the so-called Takagi-Sugeno (T-S) fuzzy model has been quite popular due to its convenient and simple dynamic structure as well as its capability of approximating any smooth nonlinear function to any specified accuracy within any compact set. In terms of such a model, the performance analysis and the design of controllers and filters play important roles in the research of fuzzy systems. In this paper, we aim to survey some recent advances on the T-S fuzzy control and filtering problems with various network-induced phenomena. The network-induced phenomena under consideration mainly include communication delays, packet dropouts, signal quantization, and randomly occurring uncertainties (ROUs). With such network-induced phenomena, the developments on T-S fuzzy control and filtering issues are reviewed in detail. In addition, some latest results on this topic are highlighted. In the end, conclusions are drawn and some possible future research directions are pointed out.This work was supported in part by the National Natural Science Foundation of China under Grants 61134009, 61329301, 11301118 and 61174136, the Natural Science Foundation of Jiangsu Province of China under Grant BK20130017, the Fundamental Research Funds for the Central Universities of China under Grant CUSF-DH-D-2013061, the Royal Society of the U.K., and the Alexander von Humboldt Foundation of Germany

Multiple input control strategies for robust and adaptive climate engineering in a low order 3-box model

A low-order 3-box energy balance model for the climate system is employed with a multivariable control scheme for the evaluation of new robust and adaptive climate engineering strategies using solar radiation management. The climate engineering measures are deployed in three boxes thus representing northern, southern and central bands. It is shown that, through heat transport between the boxes, it is possible to effect a degree of latitudinal control through the reduction of insolation. The approach employed consists of a closed-loop system with an adaptive controller, where the required control intervention is estimated under the RCP4.5 radiative scenario. Through the online estimation of the controller parameters, adaptive control can overcome key issues related to uncertainties of the climate model, the external radiative forcing and the dynamics of the actuator used. In fact, the use of adaptive control offers a robust means of dealing with unforeseeable abrupt perturbations, as well as the parametrization of the model considered, to counteract the RCP4.5 scenario, while still providing bounds on stability and control performance. Moreover, applying multivariable control theory also allows the formal controllability and observability of the system to be investigated in order to identify all feasible control strategies

Robust optimization for energy transactions in multi-microgrids under uncertainty

Independent operation of single microgrids (MGs) faces problems such as low self-consumption of local renewable energy, high operation cost and frequent power exchange with the grid. Interconnecting multiple MGs as a multi-microgrid (MMG) is an effective way to improve operational and economic performance. However, ensuring the optimal collaborative operation of a MMG is a challenging problem, especially under disturbances of intermittent renewable energy. In this paper, the economic and collaborative operation of MMGs is formulated as a unit commitment problem to describe the discrete characteristics of energy transaction combinations among MGs. A two-stage adaptive robust optimization based collaborative operation approach for a residential MMG is constructed to derive the scheduling scheme which minimizes the MMG operating cost under the worst realization of uncertain PV output. Transformed by its KKT optimality conditions, the reformulated model is efficiently solved by a column-and-constraint generation (C&CG) method. Case studies verify the effectiveness of the proposed model and evaluate the benefits of energy transactions in MMGs. The results show that the developed MMG operation approach is able to minimize the daily MMG operating cost while mitigating the disturbances of uncertainty in renewable energy sources. Compared to the non-interactive model, the proposed model can not only reduce the MMG operating cost but also mitigate the frequent energy interaction between the MMG and the grid