Constructive Nonlinear Control

In this book several streams of nonlinear control theory are merged and di- rected towards a constructive solution of the feedback stabilization problem. Analytic, geometric and asymptotic concepts are assembled as design tools for a wide variety of nonlinear phenomena and structures. Di®erential-geometric concepts reveal important structural properties of nonlinear systems, but al- low no margin for modeling errors. To overcome this de¯ciency, we combine them with analytic concepts of passivity, optimality and Lyapunov stability. In this way geometry serves as a guide for construction of design procedures, while analysis provides robustness tools which geometry lacks.

Optimal H2 order-one reduction by solving eigenproblems for polynomial equations

A method is given for solving an optimal H2 approximation problem for SISO linear time-invariant stable systems. The method, based on constructive algebra, guarantees that the global optimum is found; it does not involve any gradient-based search, and hence avoids the usual problems of local minima. We examine mostly the case when the model order is reduced by one, and when the original system has distinct poles. This case exhibits special structure which allows us to provide a complete solution. The problem is converted into linear algebra by exhibiting a finite-dimensional basis for a certain space, and can then be solved by eigenvalue calculations, following the methods developed by Stetter and Moeller. The use of Buchberger's algorithm is avoided by writing the first-order optimality conditions in a special form, from which a Groebner basis is immediately available. Compared with our previous work the method presented here has much smaller time and memory requirements, and can therefore be applied to systems of significantly higher McMillan degree. In addition, some hypotheses which were required in the previous work have been removed. Some examples are included.

Construction of nonparametric Bayesian models from parametric Bayes equations

We consider the general problem of constructing nonparametric Bayesian models on infinite-dimensional random objects, such as functions, infinite graphs or infinite permutations. The problem has generated much interest in machine learning, where it is treated heuristically, but has not been studied in full generality in non-parametric Bayesian statistics, which tends to focus on models over probability distributions. Our approach applies a standard tool of stochastic process theory, the construction of stochastic processes from their finite-dimensional marginal distributions. The main contribution of the paper is a generalization of the classic Kolmogorov extension theorem to conditional probabilities. This extension allows a rigorous construction of nonparametric Bayesian models from systems of finite-dimensional, parametric Bayes equations. Using this approach, we show (i) how existence of a conjugate posterior for the nonparametric model can be guaranteed by choosing conjugate finite-dimensional models in the construction, (ii) how the mapping to the posterior parameters of the nonparametric model can be explicitly determined, and (iii) that the construction of conjugate models in essence requires the finite-dimensional models to be in the exponential family. As an application of our constructive framework, we derive a model on infinite permutations, the nonparametric Bayesian analogue of a model recently proposed for the analysis of rank data.

Direct temperature mapping of nanoscale plasmonic devices.

Side by side with the great advantages of plasmonics in nanoscale light confinement, the inevitable ohmic loss results in significant joule heating in plasmonic devices. Therefore, understanding optical-induced heat generation and heat transport in integrated on-chip plasmonic devices is of major importance. Specifically, there is a need for in situ visualization of electromagnetic induced thermal energy distribution with high spatial resolution. This paper studies the heat distribution in silicon plasmonic nanotips. Light is coupled to the plasmonic nanotips from a silicon nanowaveguide that is integrated with the tip on chip. Heat is generated by light absorption in the metal surrounding the silicon nanotip. The steady-state thermal distribution is studied numerically and measured experimentally using the approach of scanning thermal microscopy. It is shown that following the nanoscale heat generation by a 10 mW light source within a silicon photonic waveguide the temperature in the region of the nanotip is increased by ∼ 15 °C compared with the ambient temperature. Furthermore, we also perform a numerical study of the dynamics of the heat transport. Given the nanoscale dimensions of the structure, significant heating is expected to occur within the time frame of picoseconds. The capability of measuring temperature distribution of plasmonic structures at the nanoscale is shown to be a powerful tool and may be used in future applications related to thermal plasmonic applications such as control heating of liquids, thermal photovoltaic, nanochemistry, medicine, heat-assisted magnetic memories, and nanolithography.

Stable dynamic walking over uneven terrain

We propose a constructive control design for stabilization of non-periodic trajectories of underactuated robots. An important example of such a system is an underactuated "dynamic walking" biped robot traversing rough or uneven terrain. The stabilization problem is inherently challenging due to the nonlinearity, open-loop instability, hybrid (impact) dynamics, and target motions which are not known in advance. The proposed technique is to compute a transverse linearization about the desired motion: a linear impulsive system which locally represents "transversal" dynamics about a target trajectory. This system is then exponentially stabilized using a modified receding-horizon control design, providing exponential orbital stability of the target trajectory of the original nonlinear system. The proposed method is experimentally verified using a compass-gait walker: a two-degree-of-freedom biped with hip actuation but pointed stilt-like feet. The technique is, however, very general and can be applied to a wide variety of hybrid nonlinear systems. © The Author(s) 2011.