Stability and stability robustness of multivariable Smith predictors are analysed by viewing Smith predictors as instances of Internal Model Control. This allows a much simpler development than appears in previous analyses, and the way that delays enter the plant transfer function matrix is unrestricted. It is shown that robustness to additive plant perturbations can be predicted during design,...

1. Linear Multivariable Systems 1.1. Emergence of State Space Approach 1.2. Discrete-time Control 1.3. Riccati Equation and Stabilization for Continuous-time Systems 1.4. Design Procedure 1.5. Static Output Feedback and Dynamic Compensation 1.6. Servo Control and Internal Model Principle 1.7. Design and Analysis based on Frequency Response 1.8. Control System Example 2. Control System Example 2...

This paper introduces the gstat package for the S language (R, S-PLUS). The package provides multivariable geostatistical modelling, prediction and simulation, as well as several visualisation functions. Gstat (http://www. gstat.org) was started 10 years ago and was released under the GPL in 1996; it is closely linked to several GIS systems. It was not initially written for teaching purposes, b...

The situation and trends in the application of fuzzy logic to control multi-input/multi-output (MIMO) systems are analyzed. The basic steps in designing a control system are considered. Fuzzy control applications are either knowledge-based or model-based. In model-based approaches, the first step is process modeling: Usually, interpolation and universal approximation are the two main features t...

Adaptive control refers to the control of systems that have poorly known parameters but a well modeled structure. The adaptive control of linear, time-invariant systems is well understood. However, for systems with multiple inputs and multiple outputs the adaptive controller is of high order and complex making the approach inapplicable in a number of practical problems. In this thesis a new app...

An MIMO auto-tuning method is develop that can be used by a layman of control. The method is based on MIMO identification and robust control design. The identification part delivers process model and model error bounds. The controller design block performs control synthesis, simulation and robust analysis. All steps can be done automatically. The parameters the user needs to enter are minimal a...

Let M be a complex matrix of rank one, i.e. M = pq′ where p, q are complex nby-1 matrices and ′ denotes Hermitean conjugation. Let μC(M) and μR(M) denote the structured singular values μ(M,∆) of M defined with ∆ = ∆C and ∆ = ∆R respectively, where ∆C is the cone of all diagonal matrices with complex entries, and ∆R is the cone of all diagonal matrices with real entries. (a) Express μC(M) and μR...

The contribution is focused on a control design and simulation of multi input output (MIMO) linear continuous-time systems. Suitable and efficient tools for description and controller derivation are algebraic notions as rings, polynomial matrices, and Diophantine equations. The generalized MIMO PI controller design is studied for stable and unstable systems. A unified approach through matrix Di...