A model-based method is proposed in this paper for algorithmic generation of diagnosers in coloured Petri net (CPN) form from characteristic input-output traces obtained from a qualitative model of lumped process systems. The qualitative model contains the description of the considered persistent faults in the form of fault indicators, and it is transformed into a CPN. The diagnosers are constr...

Algorithm design may be defined as the task of finding an efficient data and control structure that implements a given inputoutput specification. This paper describes a methodology for control structure design, applicable to combinatorial algorithms involving search or minimization. The methodology includes an abstract process representation based on generators, constraints, mappings and orderi...

We discuss a range of modeling choices that arise when constructing an end-to-end differentiable programming language suitable for learning programs from inputoutput examples. Taking cues from programming languages research, we study the effect of memory allocation schemes, immutable data, type systems, and builtin control-flow structures on the success rate of learning algorithms. We build a r...

This paper is concerned with state-space realizations of the adjoints of the variationals of Hamiltonian control systems. It will be shown that the variational systems of a class of Hamiltonian systems have self-adjoint state-space realizations, that is, the variational system and its adjoint have the same state-space realizations. This implies that the inputoutput mapping of the adjoint of the...

In this work we give a concise definition of information loss from a system-theoretic point of view. Based on this definition, we analyze the information loss in memoryless inputoutput systems subject to a continuous-valued input. For a certain class of multiple-input, multiple-output systems the information loss is quantified. An interpretation of this loss is accompanied by upper bounds which...

This paper deals with the optimal solution to the sampled-data minimum variance filtering problem for linear systems with noise in the states and in the measurements. The solution is derived in the time-domain by using a fast sampling zeroorder hold input discretization of the continuous time systems together with a lifting technique. The original sampled-data system is transformed into an equi...

Unstable dynamical systems can be viewed from a variety of perspectives. We discuss the potential of an inputoutput map associated with an unstable system to represent a bounded map from L2(R) to itself and then develop criteria for optimal reduced order approximations to the original (unstable) system with respect to an L2-induced Hilbert-Schmidt norm. Our optimality criteria extend the Meier-...

The general mathematical problem of fuzzy control is an interpolation problem: a list of fuzzy input-output data, usually provided by a list of linguistic control rules, should be realized as argument-value pairs for a suitably chosen fuzzy function. However, contrary to the usual understanding of interpolation, in the actual approaches this interpolation problem is considered as a global one: ...

In applying nonlinear model-predictive control to fast unstable systems, the main difficulty is that the optimization cannot be finished within one sampling interval. To solve this problem, a cascade-control scheme has been proposed, where input-output feedback linearization forms the inner loop and nonlinear predictive control the outer loop. Thus, the nonlinear predictive control has to handl...

This paper presents a new generalized approach to the singularity analysis of a general mechanism (arbitrary kinematic chain), considered as a non-redundant inputoutput device with equal number of inputs and outputs. The instantaneous kinematics of a mechanism is described by means of a velocity equation, explicitly including not only the input and output velocities but also the passive-joint v...