Neural network black-box modeling is usually performed using nonlinear inputoutput models. The goal of this paper is to show that there are advantages in using nonlinear state-space models, which constitute a larger class of nonlinear dynamical models, and their corresponding state-space neural predictors. We recall the fundamentals of both input-output and state-space black-box modeling, and s...

This paper proposes on-line optimal operation planning and control of cogeneration systems (CGS). CGS is usually connected to various facilities such as refrigerators, reservoirs, and cooling towers. In order to generate optimal operation planning for CGS, startup/shutdown status and/or input/output values of the facilities for each control interval should be determined. The facilities may have...

OFDM communications require extreme linearity of High Power Amplifiers (HPA) to avoid Inter-Carrier Interference (ICI) and subsequent degradation of the BER and Quality of Service (QoS). Amplitude (AM/AM) and Phase (AM/PM) amplifier non-linearities can be compensated in a number of ways. Nevertheless, digital adaptive schemes based on least squares optimization criteria need estimate the delay ...

In the distributed test architecture, a system with multiple ports is tested using a tester at each port/interface, these testers cannot communicate with one another and there is no global clock. Recent work has defined an implementation relation for testing against an inputoutput transition system in the distributed test architecture. However, this framework placed no restrictions on the test ...

This paper studies the partially observed stochastic optimal control problem for systems with state dynamics governed by Partial Differential Equations (PDEs) that leads to an extremely large problem. First, an open-loop deterministic trajectory optimization problem is solved using a black box simulation model of the dynamical system. Next, a Linear Quadratic Gaussian (LQG) controller is design...

A model predictive control strategy for a concentrated solar thermal power plant is proposed. Design of the proposed controller is based on an estimated linear time-invariant state space model around a nominal operating point. The model is estimated directly from inputoutput data using the subspace identification method and taking into account the frequency response of the plant. Input-output d...

In this work, three-terminal ballistic junctions, made of three-branch graphene nanoribbons (GNRs), are considered and simulated at the nanometric scale. The analysis is carried out by a scattering matrix approach, in a discrete formulation optimized for GNR devices. The ballisticity and the scattering properties of the junction contribute to the nonlinear behaviour, as, in fact, a sinusoidal v...

In this paper we provide a short overview of the Radial Basis Functions (RBF), their properties, the motivations behind their use and some of their applications. RBF’s have been employed for functional approximation in time-series modeling and in pattern classification. They have been shown to implement the Bayesian rule and to model any continuous inputoutput mapping. RBF’s are embedded in a t...

Concerned is residual generation in systems with mild nonlinearities, that is, nonlinearities which involve the inputs, outputs and faults but not the state. It is shown how structured residuals can be designed by the parity space method, in discrete time, if mild nonlinearities are present. Next a number of fundamental links between the parity space and the input-output representations are exp...

"Astructural approach to the disturbance decoupling problem of non-linear systems is introduced. For this purpose, in analogy to linear systems theory, a structural description of non-linear systems is defined. In associating a directed graph to such a system, two important system properties, the differential output rank and the structure at infinity, can be characterized in terms of inputoutpu...