An approach to optimal architectural and urban design from the energy efficiency point of view

This paper presents a new approach to architecture and urban design that results in an increase of the energy efficiency of buildings set close to each other, which is set as the optimization problem. The main goal is to maximize the sunlight impact on objects, in a way to minimize inter-object shading on each building. The problem is solved by the PSO (Particle Swarm Optimization) algorithm and its modifications, as well as the application of PSO algorithm with niches, which makes it possible to find a large number of local optima. It turned out that the PSO algorithm with niches is especially suitable for solving the described problems. The proposed methodology is illustrated by a few examples

Adaptive Parameter Estimation in LTI Systems

An adaptive algorithm solving the on-line parameter estimation problem for a broad class of linear systems is proposed. The approach can be applied to systems with delay, distributedparameter systems, fractional-order systems, and others that are stable or stabilized by linear feedback. The proposed scheme can be applied to simultaneously track sufficiently slow changes in process gains, delays, time constants, diffusivity, and other parameters. The proposed method is gradient-based, and it yields a relatively efficient numerical implementation. Convergence and robustness of the algorithm are investigated through Lyapunov analysis, yielding explicit convergence conditions that generalize the well-known “persistence of excitation” and identifiability requirements arising in conventional adaptive estimation. The method is illustrated by several examples

Complex-Order Models: A System Identification Point of View

The present paper proposes a framework for the systematic and fruitful application of complex-order operators for modeling and control applications. We emphasize that special care must be taken when using complex-order elements to ensure that their responses to real-valued stimuli are real-valued themselves. The proposed complex-order real-valued elements enable the seamless generalization of their conventional real and integer-order counterparts. We further demonstrate how any linear operator can be extended in much the same way as the differintegral, by “raising” it to a power of a complex order, while ensuring that its kernel remains real-valued. The applicability of our considerations is demonstrated by a model of a compressed natural gas injection system

Complex-Order Models: A System Identification Point of View

The present paper proposes a framework for the systematic and fruitful application of complex-order operators for modeling and control applications. We emphasize that special care must be taken when using complex-order elements to ensure that their responses to real-valued stimuli are real-valued themselves. The proposed complex-order real-valued elements enable the seamless generalization of their conventional real and integer-order counterparts. We further demonstrate how any linear operator can be extended in much the same way as the differintegral, by “raising” it to a power of a complex order, while ensuring that its kernel remains real-valued. The applicability of our considerations is demonstrated by a model of a compressed natural gas injection system