This paper presents an approach to distributed state estimation‐based control of nonlinear MIMO systems, capable of incorporating delayed measurements in the estimation algorithm while also being robust to packet losses. First, the paper examines the problem of distributed nonlinear filtering over a communication/sensors network, and the use of the estimated sta...

1. Motivation Spatio-temporal systems (STSs) described by partial differential equations (PDEs) are widely used in physical and engineering systems [1]. Traditional methods for the analysis of a PDE system rely on an analytical solution of the system, which is difficult to obtain for most nonlinear PDEs. Alternative methods such as qualitative analysis of solutions or numerical methods for an a...

Wireless communication paradigm has evolved from single-user single-input single-output (SISO) and multiple-input multiple-output (MIMO) systems to multi-user (MU) MIMO counterparts, which are shown greatly improving the rate performance by transmitting to multiple users simultaneously. The sum-capacity and the capacity region of a single-cell MU MIMO downlink system or the so-called MIMO broad...

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...

This paper considers an iterative algorithm for the identification of structured nonlinear systems. The systems considered consist of the interconnection of a MIMO linear systems and a MIMO nonlinear system. The considered interconnection structure can represent as particular cases Hammerstein, Wiener or Lur’e systems. A key feature of the proposed method is that the nonlinear subsystem may be ...

Nonlinear model-based predictive control (MBPC) in multi-input multi-output (MIMO) process control is attractive for industry. However, two main problems need to be considered: (i) obtaining a good nonlinear model of the process, and (ii) applying the model for control purposes. In this paper, recent work focusing on the use of Takagi±Sugeno fuzzy models in combination with MBPC is described. F...

Multi-user multi-input multi-output (MIMO) system has been attracting much attention due to its high spectrum efficiency. Nonlinear MIMO signal detection methods with less computational complexity have been widely studied for single-user MIMO systems. In this paper, we investigate how a lattice reduction (LR)-aided detection and a maximum likelihood detection (MLD) employing the QR decompositio...

In this paper, a robust adaptive fuzzy control algorithm is proposed for a class of nonlinear multiple-input-multiple-output (MIMO) systems with unknown interconnected functions. In the controller design, the robust control terms are used to compensate the approximation errors, which can improve robustness of the systems. The developed control algorithm overcomes the singularity problem of nonl...

The paper is concerned with the synchronization problem of a general class of multi-input multi-output (MIMO) nonlinear continuous-time systems under sampled-data output feedback control. The main contributions of the present paper are twofold: (i) we provide a unified synthesis method and synchronization criteria for MIMO Lipschitz nonlinear continuous-time systems; (ii) we present a systemati...