Low sensitivity feedback law implementation for 2-d digital systems

✍ Scribed by Peter Stavroulakis

• Publisher: Elsevier Science
• Year: 1981
• Tongue: English
• Weight: 628 KB
• Volume: 312
• Category: Article
• ISSN: 0016-0032
• DOI: 10.1016/0016-0032(81)90062-4

✦ Synopsis

The problem analyzed and studied in this paper refers to a general class of the linear time-invariant multivariable two dimensional (2-D) digital systems using state feedback. A growing interest has developed over the past few years into problems involving signals and systems that depend on more than one variable. In order to be able to give a quantitative formulation of the problem, the mathematical model is either assumed or derived. In either case there is always a discrepancy between the actual system and its mathematical model. However, once a realistic model is chosen, sensitivity plays an important role in assessing the behavior of the system or its components under varying conditions. It is shown here that using matrix minimization techniques we can derive a set of non-linear matrix equations which constitute the

necessary conditions that must be satisfied for an optimal low sensitivity solution for a general class of multivariable systems. The initial conditions of the system are assumed to be random processes with known mean and covariance and the low sensitivity input vector is implemented via state feedback.