In this paper we consider the study of the servomechanism problem for multi-input multi-output (MIMO) linear time-invariant (LTI) positive systems. In particular, we present results on the tracking problem of nonnegative constant reference signals for unknown stable MIMO positive LTI systems with nonnegative constant disturbances. Our results exploit the structure of tuning regulators and show ...

In this study, a Multi-Objective Genetic Algorithm (MOGA) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear Multi-input Multi-output (MIMO) systems. In the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. Furthermore, se- curing low-level and high-level ...

In this paper, we present a new adaptive error-cancellation (AEC) technique, denoted as multi-input–multi-output (MIMO)-AEC, for the design of low-power MIMO signal processing systems. The MIMO-AEC technique builds on the previously proposed AEC technique by employing an algorithm transformation denoted as MIMO decorrelating (MIMO-DECOR) transform. MIMO-DECOR reduces complexity by exploiting co...

A multi-input and multi-output optimal controller for stochastic systems with time-varying dynamics is developed. The system to be controlled is described using a multi-input and multi-output time-varying autoregressive moving average model with multiple delays. The controller minimises a generalised minimum variance cost functional that is the sum of quadratic output tracking error variances a...

1. Introduction The multi-input multi-output (MIMO) technique incorporating space-time coding is a candidate for the next generation high performance wireless communication systems. The MIMO technique employs multiple-element antennas to establish spatial subchannels to improve spectrum efficiency. The promised increase in channel capacity by MIMO is possible only if rich-scattering is present ...

The identification of nonlinear multi-input multi-output (MIMO) processes is important and challenging problem. Fuzzy systems have been effectively used to identify complex nonlinear dynamical systems, but mostly single-input single-output systems are considered. This paper presents a compact Takagi-Sugeno fuzzy model that can be effectively used to represent MIMO dynamical systems. For the ide...

Adaptive inverse control is an automatic control-system design method which “learns” over time how to control a dynamic system (“plant”). The technique may be applied to single-input single-output (SISO) and multi-input multi-output (MIMO) plants. The plant may be linear or nonlinear. This report addresses preliminary results concerning a new way to perform adaptive inverse control of linear MI...

Multi-Input Multi-Output (MIMO) transmission technique, in which both transmitter and receiver are equipped with multiple antennas, is attracting attention due to its many advantages such as its throughput improvement. For this reason, various cellular mobile radio systems based on MIMO have been developed such as 3GPP LTE (Long Term Evolution) [1] and Mobile WiMAX [2]. MIMO technique is also a...

This article presents a tutorial on multiuser multiple-antenna wireless systems with a very large number of antennas, known as massive multi-input multi-output (MIMO) systems. Signal processing challenges and future trends in the area of massive MIMO systems are presented and key application scenarios are detailed. A linear algebra approach is considered for the description of the system and da...