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In this chapter an algorithm for nonlinear explicit model predictive control is presented. A low complexity receding horizon control law is obtained by approximating the optimal control law using multiscale basis function approximation. Simultaneously, fea ...
This paper presents a digital, transistor level implemented neo-fuzzy neural network. This type of neural network is particularly well suited for real-time applications like those encountered in signal processing and nonlinear system identification. We con ...
This paper addresses the problem of evaluating and estimating the mechanical robustness of footholds for legged robots in unstructured terrain. In contrast to approaches that rely on human expert knowledge or human defined criteria to identify appropriate ...
This paper presents an application of the kernel principal component analysis aiming at aligning optical images before the application of change detection techniques. The approach relies on the extraction of nonlinear features from a selected subset of pix ...
In non-iterative data-driven controller tuning, a set of measured input/output data of the plant is used directly to identify the optimal controller that minimizes some control criterion. This approach allows the design of fixed-order controllers, but lead ...
In this thesis, we investigate a hierarchical approach for estimating the phonetic class-conditional probabilities using a multilayer perceptron (MLP) neural network. The architecture consists of two MLP classifiers in cascade. The first MLP is trained in ...
Integral observers are useful tools for estimating the plant states in the presence of non-vanishing disturbances resulting from plant-model mismatch and exogenous disturbances. It is well known that these observers can eliminate bias in all states, given ...
This paper focuses on urban environmental system identification. Wind-flow modeling is a challenging task because of simplifications of complex processes as well as geometry simplifications. Even a more detailed model may not be accurate because of uncerta ...
Institute of Electrical and Electronics Engineers ( IEEE )2013
The paper presents a procedure for parameter identification along with its application to the model of a combined cycle power plant that includes the surrounding electrical network, built for the analysis of islanding maneuvers transients. The paper illust ...
In this paper an algorithm for nonlinear explicit model predictive control is introduced based on multiresolution function approximation that returns a low complexity approximate receding horizon control law built on a hierarchy of second order interpolets ...
