In the last years, the success of kernel-based regularisation techniques in solving impulse response modelling tasks has revived the interest on linear system identification. In this work, an alternative perspective on the same problem is introduced. Instead of relying on a Bayesian framework to include assumptions about the system in the definition of the covariance matrix of the parameters, h...

This two-part paper presents modelling and scheduling approaches of flexible manufacturing systems using Petri nets (PNs) and artificial intelligence (AI)-based heuristic search methods. In Part I, PN-based modelling approaches and basic AI-based heuristic search algorithms were presented. In Part II, a new heuristic function that exploits PN information is proposed. Heuristic information obtai...

Many robot systems employ logic based or reactive controllers making them hybrid systems (i.e mixed discretecontinuous). However, designing such control laws in a systematic manner remains a challenging task. In this case study, we apply the formal modelling paradigm to a team of mobile robots. The linear hybrid automata modelling framework is used to describe the high-level design, and the ver...

The paper deals with the application of evolutionary algorithms to black-box optimization, frequently encountered in biology, chemistry and engineering. In those areas, however, the evaluation of the black-box fitness is often costly and time-consuming. Such a situation is usually tackled by evaluating the original fitness only sometimes, and evaluating its appropriate response-surface model ot...

The last decade has seen max-stable processes emerge as a common tool for the statistical modelling of spatial extremes. However, their application is complicated due to the unavailability of the multivariate density function, and so likelihood-based methods remain far from providing a complete and flexible framework for inference. In this article we develop inferentially practical, likelihood-...

ii using them to find global minimum point of seven well-known benchmark functions commonly used in development of optimisation techniques development. The results show that all ABFAs achieve better accuracy and speed compared to those of SBFA. The ABFAs are then used in modelling and control of a single-link flexible manipulator system. This includes modelling (based on linear model structures...

Because of random nature of many dependent variables in coastal engineering, treatment of effective parameters is generally associated with uncertainty. Numerical models are often used for dynamic analysis of complex structures, including mechanical systems. Furthermore, deterministic models are not sufficient for exact anticipation of structure’s dynamic response, but probabilistic models...