Disturbances rejection is an important field of control theory. In this context, our paper is proposed to deal with asymptotic rejection of periodic disturbances affecting discrete multivariable systems with an interactor matrix. A multivariable repetitive sliding mode control is proposed to cancel the disturbances when the system is nondecouplable. To synthesis this control an interactor matrix is used. A numerical example shows that the proposed strategy gives good performance in terms of rejecting periodic disturbances for nondecouplable multivariable systems.

 On-line parameter estimation over a wireless network based on sliding modes for a high fidelity simulation of a four engine transport aircraft is described in this paper. An approach using a sliding mode observer involving a second-order sliding mode 'super-twisting' injection signal to estimate changes in the drag coefficient is proposed. A peer-to-peer wireless network is considered in which one of the computers generates data from a high fidelity four engine transport aircraft model in real-time, which represents a 'virtual transport aircraft', and the other computer processes each data package to carry out on-line estimation of the drag coefficient.

 This paper presents a discrete-time variable-structure control (DTVSC) for the dynamic positioning system of a marine vessel. The DTVSC guarantees robustness with respect to environmental disturbances. Moreover, the allocation problem, in the case of vessels with azimuth thrusters, represents a challenging problem since a non-convex nonlinear problem must be solved. In this paper, the allocation problem is solved using the Damped Least Squares method. The proposed solution is compared with a PID-based control. Reported simulations show that the proposed solution produces better performance.

 The main result of our new method is to convert an output constraint into an input constraint for a nonlinear system. Then, standard saturated input design can be used as an anti-windup design for instance which is known to be efficient to enlarge a closed-loop system stability domain in presence of control saturations. We only address the single input single 'saturated' output problem in this paper.

 This paper proposes an efficient nonlinear predictive controller (NMPC) for application to a power plant drum-boiler. The control objectives are to maintain the water and pressure levels in the drum within a desired range. First, the nonlinear model of the drum-boiler is transformed to LTV state-dependent nonlinear form to provide global nonlinear behavior. Next, state-dependent nonlinear Kalman filter is used to estimate the system states. Then, a supervisory NMPC algorithm is used as a second level controller to generate optimal set points to the lower level regulating PID loops while maintaining output constraints. Simulation results are presented to demonstrate the excellent tracking and disturbance rejection performance compared with a stand-alone multi-loop PID controllers.