Ricard Villà

Managing quality-of-control in network-based control systems by controller and message scheduling co-design

In network-based control systems (NCSs), plant sensor-controller-actuator nodes in closed-loop operation drive principal network traffic. The quality-of-control (QoC) in an NCS, i.e., the performance delivered by each closed-loop operation, depends not only on the controller design but also on the message scheduling strategy. In this paper, we show that the co-design of adaptive controllers and feedback scheduling policies allows for the optimization of the overall QoC. First, we discuss the limitations of standard discrete-time control models for controllers of control loops that are closed over communication networks. Afterwards, we describe an approach to adaptive controllers for NCS that: 1) overcomes some of the previous restrictions by online adapting the control decisions according to the dynamics of both the application and executing platform and 2) offers capabilities for dynamic management of QoC through message scheduling.

Self-triggered networked control systems: An experimental case study

A self-triggered controller is characterized, in general, by a non-periodic sequence of job activations. And each job execution, apart from performing sampling, control algorithm computation and actuation, calculates the next job activation time as a function of the plant state. This paper describes the implementation of self-triggered controllers in networked control systems (NCS). The implementation corroborates that self-triggered control can be used for minimizing bandwidth utilization while providing similar control performance than periodic controllers.

Stability of On-line Compensated Real-time Scheduled Control Tasks

Abstract Real-time scheduling methods introduce various types of jitter in task instance execution. For real-time computer-controlled systems, the introduced sampling jitter and sampling-actuation delays may degrade the system performance and even lead to instability in the system. The degradation of the system performance can be compensated on-line by updating the controller parameters at each controller task instance execution, in what we call the compensation approach. In this paper we present stability analysis for controller tasks that perform the compensation approach.

Object-oriented modeling for remote monitoring of manufacturing processes

Deals with the use of object oriented technologies in the modeling of industrial plants that have to be remotely monitored and/or controlled. The main goal is to propose a design methodology for obtaining the model of the so-called Virtual Plant, that a remote and certified user will use to access the real plant for performing command actions and/or monitoring. The type of applications and systems targeted must have autonomous behavior and be interconnected and accessible. Reliability, maintainability and flexibility are also required goals, as well as a high rate of reusability of the applications. The methodology has been applied to the remote process monitoring and control of manufacturing processes. The Virtual Plant Model is, in fact, the part of the plant that can be accessed by a certified remote client and thus it can be constituted by a set of sub-models, as many as different types of clients. The Virtual Plant resides inside the Application Server who is responsible of communicating with the cell controller and sends the image of the actual plant state (the Virtual Plant) as required by the remote client (monitoring) or sends the client commands to the cell controller.

A probabilistic approach to the stability analysis of real-time control systems

Abstract In real-time multitasking systems, feasible periodic tasks execute within their periods. However, the exact time at which each task executes vary due to other task interferences. For control tasks, this produces irregular sampling and varying time delays, which may degrade system performance and bring the system to instability. In this paper we present stability conditions that allow us to evaluate if a closed-loop system designed to work at a nominal sampling period h d with a nominal time delay τ d will remain stable if the run-time sampling is not strictly periodic and time delays vary randomly. In the closed-loop system model, we consider the irregular sampling and the varying time delays as random variables with known expectation. With this model, the system evolution can be seen as a sequence of random state vectors generated by the system closed-loop matrix. Then, we derive stability conditions for the system in terms of convergence of a sequence of random variables.

Real Time Scheduling Methods Requirements in Distributed Control Systems

Abstract Distributed control systems involve three main disciplines: control systems, real time systems, and communication systems. Control systems, due their stringent timing constraints, demand real time computing technology. Distributed control systems need communication systems when distributing sensors, actuators, the control procedures and data messaging. In general, demands of distributed control systems and properties of real time scheduling algorithms differ, for example, for activation patterns of tasks. The aim of this paper is to provide a set of requirements to overcome current limitations of real time scheduling methods to their increase applicability for distributed control systems

Hands-on course in networked control systems

This paper presents a hands-on course in networked control systems (NCS) to be integrated in the education of embedded control systems engineers. The course activities have a strong practical component and most of them are applied exercises to be implemented in a NCS setup. The paper describes the experimental setup and then proposes several activities that can be shaped into a course program according to the needs and diverse background of the targeted audience.