This work addresses the problem of stabilizing uncertain systems with quantized outputs using the supervisory control framework, in which a finite family of candidate controllers is employed together with an estimator-based switching logic to select the active controller at every time. For static quantizers, we provide a relationship between the quantization range and the quantization error bou...

A supervisory controller for discrete-event (DE) systems is presented that uses a novel matrix formulation. This matrix formulation makes it direct to write down the DE controller from standard manufacturing tools such as the bill of materials or the assembly tree. The matrices also make it straightforward to actually implement the DE controller on a manufacturing workcell for sequencing the jo...

In this paper a framework for engineering supervisory controllers product lines with dynamic feature configuration is proposed. The variability in valid configurations described by model. Behavior of system components achieved using (extended) finite automata and both behavioral constraints are expressed means requirements as common control theory. Supervisory controller synthesis applied to co...

A supervisory controller for Discrete Event (DE) Systems is presented that uses a novel Matrix Formulation. This matrix formulation makes it direct to write down the DE controller from standard manufacturing tools such as the Bill of Materials or the assembly tree. The matrices also make it straightforward to actually implement the DE controller on a manufacturing workcell for sequencing the jo...

Hybrid control systems contain two distinct types of systems, continuous state and discrete-state, that interact with each other. Their study is essential in designing sequential supervisory controllers for continuous-state systems, and it is central in designing control systems with high degree of autonomy. After an introduction to intelligent autonomous control and its relation to hybrid cont...

Using neural network to identify a function in the dynamic equation brings about additional difficulties which are not generic in the other function approzimation problems. First, training samples can not be arbitrarily chosen due to hard nonlinearity, so are apt to be nonuniform over the region of interest. Second, the system may become unstable while attempting t o obtain the samples. This pa...

pto Centre National de la Recherche Scientifique Institut National de Recherche en Informatique (UMR 6074) Université de Rennes 1 – Insa de Rennes et en Automatique – unité de recherche de Rennes Supervisory Control of Discrete or Hybrid Symbolic systems Abstract In this paper we tackle the safety controller synthesis problem for various models ranging from nite transition systems to hybrid sys...

The complexity of the design supervisory controllers for today’s high-tech systems is ever increasing with rise in demands higher safety and functionality. Supervisory control synthesis enables engineer to automatically generate a controller from model plant requirements. Although theory an active research area, number industrial applications remains relatively low. One main reasons this lack g...

Cyber-physical systems (CPS), such as autonomous vehicles crossing an intersection, are vulnerable to cyber-attacks and their safety-critical nature makes them a target for malicious adversaries. This paper studies the problem of supervisory control of autonomous intersections in the presence of sensor attacks. Sensor attacks are performed when an adversary gains access to the transmission chan...

We study the problem of adaptively stabilizing time-varying plants using supervisory control, which employs multiple controllers and a supervisory unit that orchestrates switching among the controllers. We show that for bounded disturbances and noise, all the closed-loop signals remain bounded provided that the plant varies slowly enough and the unmodeled dynamics are small enough. Slow variati...