Analytical results for the multi-objective design of model-predictive control

In model-predictive control (MPC), achieving the best closed-loop performance under a given computational resource is the underlying design consideration. This paper analyzes the MPC design problem with control performance and required computational resource as competing design objectives. The proposed multi-objective design of MPC (MOD-MPC) approach extends current methods that treat control performance and the computational resource separately -- often with the latter as a fixed constraint -- which requires the implementation hardware to be known a priori. The proposed approach focuses on the tuning of structural MPC parameters, namely sampling time and prediction horizon length, to produce a set of optimal choices available to the practitioner. The posed design problem is then analyzed to reveal key properties, including smoothness of the design objectives and parameter bounds, and establish certain validated guarantees. Founded on these properties, necessary and sufficient conditions for an effective and efficient solver are presented, leading to a specialized multi-objective optimizer for the MOD-MPC being proposed. Finally, two real-world control problems are used to illustrate the results of the design approach and importance of the developed conditions for an effective solver of the MOD-MPC problem

Dynamics and control of thermoacoustic instability

© 2009 Dr. William H. MoaseThe use of lean, premixed combustion in gas turbines is now widespread due to their low NOx emissions. Such systems are, however, susceptible to a phenomenon called thermoacoustic instability, which occurs as a result of unstable coupling between the combustion chamber acoustics and the flame. It can lead to large amplitude pressure oscillations within a combustor at frequencies in the hundreds of hertz. These pressure oscillations can result in unacceptably large noise levels, flame blow-out, reduced performance and fatigue failure of the combustor walls. This thesis investigates two problems of particular relevance to thermoacoustic instability. (For complete abstract open document

Semi-global stability analysis of a discrete-time extremum-seeking scheme using LDI methods

Abstract—This paper presents and analyses a new formula-tion of extremum-seeking control for discrete-time systems. As-suming a static, strongly convex SISO plant, a novel method of analysis using Linear Difference Inclusions (LDI) demonstrates semi-global stability of the control scheme. Furthermore, given limited information about the plant mapping, it is shown how the LDI system description allows a conservative upper bound on the adaptation gain to be evaluated, improving convergence speed. I

Fast model-based extremum seeking on Hammerstein plants

Abstract—Partial plant knowledge may be used to develop model-based extremum seekers, however existing results rely on a type of time-scale separation which leads to slow optimization relative to the plant dynamics. In this work, a fast model-based extremum seeking scheme is proposed for a Hammerstein plant, and semi-global stability results are provided. Simulation results are used to validate the theoretical results. I