In this paper, the adaptive fuzzy backstepping output feedback tracking control problem is considered for a class of uncertain stochastic multi-input and multi-output (MIMO) nonlinear systems in pure-feedback form. The stochastic MIMO nonlinear systems under study have unknown nonlinear functions, input saturation and immeasurable states. By using fuzzy logic systems to identify the uncertain n...

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...

In this thesis, Some adaptive neural control design ways are presented for a class of multi-input multi-output (MIMO) nonlinear systems in block-triangular form with disturbance input and state time-varying delay. Neural networks are employed to approximate the unknown continuous functions. By combining the use of a novel quadratictype Lyapunov-Krasovskii functionals and adaptive NN backsteppin...

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...

This paper presents a method to control height and speed of fixed wing unmanned aerial vehicles (UAVs) using MATLAB platform. The mathematical dynamic model of Six Degrees of Freedom (6-DOF) aircraft is nonlinear and it is linearized about a flight condition. System is divided into two Multi Input Multi Output (MIMO) sub models. First model controls the longitudinal dynamics and second model is...

Abstract This paper addresses the adaptive passivation of multi-input multi-output (MIMO) non-linear systems,with unknown parameters. The class of MIMO non-linear systems considered here has an explicit linear parametric uncertainty and it is made equivalent to a passive system by means of an adaptive controller with adaptive laws specially designed, which include suitable time-varying gains. T...

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...

0957-4174/$ see front matter 2010 Elsevier Ltd. A doi:10.1016/j.eswa.2010.09.118 ⇑ Corresponding author. Tel.: +91 431 2503104; fax E-mail addresses: [email protected] (R. Jain), n [email protected] (T.K. Radhakrishnan). Nonlinearities present in the systems make their controller design a non-trivial task. The difficulty further increases in case of multi-input–multi-output (MIMO) systems wi...

Because of the existing interactions among the variables of a multiple input-multiple output (MIMO) nonlinear system, its identification is a difficult task, particularly in the presence of uncertainties. Cement rotary kiln (CRK) is a MIMO nonlinear system in the cement factory with a complicated mechanism and uncertain disturbances. The identification of CRK is very important for different pur...