In order to effectively control the multi-input multi-output (MIMO) characteristics of a boiler-turbine unit Fuzzy model predictive control (FMPC) has been previously applied successfully. An important step in the FMPC design is the partitioning (also called the design of the antecedent rules). In this work it is shown that by exploiting the plant characteristics and by using suitable metrics o...

This paper presents two nonlinear model-based control designs for a hydraulic system that consists of two mechanically coupled hydraulic cylinders actuated each by a separate servo-valve. Based on a physically-oriented nonlinear mathematical model of the test rig, a further model simplification results in a completely controllable MIMO system. Two different control structures are discussed and ...

The problem of identification of a nonlinear dynamic system by using multiple-input and multiple-output flexible neural tree (MIMO-FNT) is presented in this paper. This work is an extension of our previously multiple-input and singleoutput FNT model. FNT is a tree-structured neural networks which allows input variables selection, over-layer connections and different activation functions for dif...

This paper presents an indirect adaptive fuzzy control scheme for a class of unknown multi-input multi-output (MIMO) nonlinear systems with external disturbances. Within this scheme, the dynamic fuzzy logic system (DFLS) is employed to identify the unknown nonlinear MIMO systems. The control law and parameter adaptation laws of DFLS are derived based on the Lyapunov synthesis approach. The cont...

In this paper, adaptive neural control is proposed for a class of multi-input multi-output (MIMO) nonlinear unknown state time-varying delay systems in block-triangular control structure. Radial basis function (RBF) neural networks (NNs) are utilized to estimate the unknown continuous functions. The unknown time-varying delays are compensated for using integral-type Lyapunov-Krasovskii function...

In this paper, the robust tracking control scheme is proposed for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems with input saturation and unknown external disturbance based on the recurrent wavelet neural network disturbance observer (RWNNDO) and the backstepping technique. And then, the developed robust tracking control scheme is applied to an unmanned aerial vehic...

At the end of the 19th century Liouville and Riemann introduced the notion of a fractional-order derivative, and in the latter half of the 20th century the concept of the so-called Grünewald-Letnikov fractional-order discrete difference has been put forward. In the paper a predictive controller for MIMO fractional-order discrete-time systems is proposed, and then the concept is extended to nonl...

This work concerns general multiple-input/multiple-output (MIMO) nonlinear systems with nonsingular characteristic matrix. For these systems, the problem of inversion is revisited and explicit formulas are derived for the full-order and the reduced inverse system. The reduced inverse naturally leads to an explicit calculation of the unforced zero dynamics of the system and the definition of a c...

For a typical MIMO (Multiple-Input Multiple-Output) nonlinear dynamic system, fault detection and isolation usually aim at process faults with an assumption that actuator faults and sensor faults do not occur at the same time, which is not always the case. This paper uses Extended State Observer for real-time process fault detection and fuzzy inference for fault isolation. It then investigates ...