Optimal integrated control and scheduling of networked control systems with communication constraints: application to a car suspension system

Abstract

Abstract-This paper addresses the problem of the optimal control and scheduling of Networked Control Systems over limited bandwidth deterministic networks. Multivariable linear systems subject to communication constraints are modeled in the Mixed Logical Dynamical (MLD) framework. The translation of the MLD model into the Mixed Integer Quadratic Programming (MIQP) formulation is described. This formulation allows the solving of the optimal control and scheduling problem using efficient branch and bound algorithms. Advantages and drawbacks of on-line and off-line scheduling algorithms are discussed. Based on this discussion, a computationally efficient on-line scheduling algorithm, which can be seen as a compromise, is presented and its performance is evaluated. Finally, this algorithm, called Optimal Pointer Placement (OPP) scheduling algorithm, is applied to the control and scheduling of a car suspension system.

Reducing usage of the computational resources by event driven approach to model predictive control

“…A basic MPC law is described by the following algorithm Algorithm 1 -calculation of the basic MPC [3] 1. Get the new state x(k).…”

“…One of the most critical of them, especially when realtime systems are of concern, may be the computational complexity. This issue can be addressed by different approaches, one of such method is introduced in [3] and [4]. In [4] is presented optimal control and scheduling designed on constrained computer system using both online and off-line technique.…”

Kalman Filtering with Optimally Scheduled Measurements in Bandwidth Limited Communication Media

“…The problem of designing a controller with a focus on communication constraints was introduced in [3], [6] and [7]. Meanwhile, [6]- [8] examined state estimation and control.…”

“…Previously reported results on optimal scheduling include numerical optimization approaches for offline optimal selection of periodic communication sequences through genetic algorithms and particle swarm optimization [6], heuristic approaches based on tree pruning [7], and a predictive online scheduling scheme [3]. The latter scheme solves an online optimization problem through a branch and bound method, or the so-called optimal pointer placement, which is a semi-online simplified version of the problem [3].…”

“…The latter scheme solves an online optimization problem through a branch and bound method, or the so-called optimal pointer placement, which is a semi-online simplified version of the problem [3].…”