Consider the controlled system dx/dt = Ax + α(t)Bu where the pair (A,B) is stabilizable and α(t) takes values in [0, 1] and is persistently exciting, i.e., there exist two positive constants μ, T such that, for every t ≥ 0, ∫ t+T t α(s)ds ≥ μ. In particular, when α(t) becomes zero the system dynamics switches to an uncontrollable system. In this paper, we address the following question: is it p...

This paper study the main theoretical properties of Quantized State Control (QSC) applied to linear time invariant (LTI) systems. Using a previous result on perturbed systems, a closed formula for the quantization design is deduced. It is shown that the mentioned formula ensures that the difference between the trajectories of the Continuous Control System (CCS) and the QSC system is bounded by ...

This paper considers the controller synthesis problem for the class of linear time-invariant L2 behaviors. We introduce classes of LTI L2 systems whose behavior can be represented as the kernel of a rational operator. Given a plant and a controlled system in this class, an algorithm is developed that produces a rational kernel representation of a controller that, when interconnected with the pl...

Model predictive control (MPC) is an advanced optimal technique to minimize a objective while satisfying set of constraints and well suited activate the building energy flexibility. The MPC controller performance depends on accuracy model prediction. Inaccurate predictions can directly lead low performance. Linear time-invariant (LTI) models are often used in buildings. However, LTI do not adap...

We consider a time-invariant, continuous system _ x = f(x; u), where f is a rational function of the state x, linear in the input u. We introduce a Linear-Fractional Representation (LFR) for the system, which consists of viewing it as an LTI system, connected with a diagonal feedback operator linear in the state. Using this representation , we devise suucient conditions for various properties t...

Skin conductance responses (SCR) are increasingly analyzed with model-based approaches that assume a linear and time-invariant (LTI) mapping from sudomotor nerve (SN) activity to observed SCR. These LTI assumptions have previously been validated indirectly, by quantifying how much variance in SCR elicited by sensory stimulation is explained under an LTI model. This approach, however, collapses ...

This study presents a new methodology for identifying near-optimal sensor locations contaminant source tracing in river networks. We define an optimal placement as one that enables the best overall reconstruction of concentrations from observed data. To establish physical basis problem, we first derive linear time-invariant (LTI) model riverine transport using one-dimensional advection-reaction...

The essential issues of time complexity and probing signal selection are studied for persistent identi!cation of linear time-invariant systems in a closed-loop setting. By establishing both upper and lower bounds on identi!cation accuracy as functions of the length of observation, size of unmodeled dynamics, and stochastic disturbances, we demonstrate the inherent impact of unmodeled dynamics o...

This paper proposes a parametric cumulant-based phase-estimation method for one-dimensional (1-D) and twodimensional (2-D) linear time-invariant (LTI) systems with only non-Gaussian measurements corrupted by additive Gaussian noise. The given measurements are processed by an optimum allpass filter such that a single M th-order (M 3) cumulant of the allpass filter output is maximum in absolute v...

In this paper, we propose a new dynamical fuzzy modeling technique for SISO complex systems. It is seen that, the whole state-space of a complex system is divided into subspaces and a linear time-invariant (LTI) model is then used tu approximate the complex system in each subspace. However, the global dynamical fuzzy model of the complex system is derived by aggregating all subsystem poles and ...