We evaluate the success of the qualitative physics enterprise in automating expert reasoning about physical systems. The eld has agreed, in essentials, upon a modeling language for dynamical systems, a representation for behavior, and an analysis method. The modeling language consists of generalized ordinary diierential equations containing unspeciied constants and monotonic functions; the beha...

Preliminary note In this paper an application of Petri nets (Petri Nets – PN) is shown in the modeling and simulation of the production process. Petri nets are graphically mathematical tools that are suitable for modeling and projecting different system types. The very approach to a system modeling by means of Petri nets faithfully reflects the way events develop in the real world so that, for ...

Constrained State-space Model Predictive Control is presented in the paper. Predictive controller based on incremental linear state-space process model and quadratic criterion is derived. Typical types of constraints are considered – limits on manipulated, state and controlled variables. Control experiments with nonlinear model of multivariable laboratory process are simulated first and real ex...

This paper considers two-dimensional (2D) discrete linear systems recursive over the upper right quadrant described by well known state-space models. Included are discrete linear repetitive processes that evolve over subset of this quadrant. A stability theory exists for these processes based on a bounded-input bounded-output approach and there has also been work on the design of stabilizing co...

With intense current interest in active noise control, it is desirable to develop models of acoustic phenomena that are useful for state-space-based control methodologies. Consequently, this paper extends the one-dimensional modeling of acoustic transfer functions developed in earlier work to the case of two-dimensional acoustics. This extension must therefore account for the phenomenon of evan...

{We describe a multiscale modeling framework applicable for a wide range of hydrologic processes. The foundation for this work has been laid by Basseville et al. 1992] and Chou et al. 1994]. Their development is based on treating the scale parameter akin to time, such that description at a particular scale captures the features of the process up to that scale that are relevant for the predictio...

This paper deals with the automatic dependability analysis of systems designed using UML. An automatic transformations is defined for the generation of models to capture systems dependability attributes, like reliability. The transformation concentrates on structural UML views, available early in the design, to operate at different levels of refinement, and tries to capture only the information...

We propose a method to optimise the parameters of a policy which will be used to safely perform a given task in a data-efficient manner. We train a Gaussian process model to capture the system dynamics, based on the PILCO framework. Our model has useful analytic properties, which allow closed form computation of error gradients and estimating the probability of violating given state space const...

We consider the problem of multi-step ahead prediction in time series analysis using the non-parametric Gaussian process model. k-step ahead forecasting of a discrete-time non-linear dynamic system can be performed by doing repeated one-step ahead predictions. For a state-space model of the form yt = f(yt 1; : : : ; yt L), the prediction of y at time t+ k is based on the estimates ŷt+k 1; : : :...