Almost all the theoretical aspects of Model Predictive Control (MPC), such as stability, recursive feasibility and even the optimality are now well established for both, the nominal and the robust case. The stability and recursive feasibility are usually guaranteed by means of additional terminal constraints, while the optimality is achieved considering closed-loop predictions. However, these s...

Predictive control of nonlinear systems subject to output and input constraints is considered. A fuzzy model is used to predict the future behavior. Two new ideas are proposed here. First, an added constraint on the applied control action is used to ensure the decrease of a quadratic Lyapunov function, and so guarantee Lyapunov exponential stability of the closed-loop system. Second, the feasib...

This paper basically follows [1], where the transfer function formalism in nonlinear control systems, both continuous and discrete-time, is discussed. Here, we demonstrate how such a formalism can be adopted to design constrained nonlinear discrete-time controller for a fluid tank system. The first step consists in finding appropriate nonlinear discrete-time description for a fluid tank system,...

A higher order sliding fuzzy type-2 controller scheme for an nth order multi-input multi-output (MIMO) nonlinear uncertain perturbed systems is proposed in the paper. To overcome the constraint on the knowledge of the system model, local models related to some operating points were used to synthesize a nominal fuzzy type-2 global model. The controller uses integral sliding mode concept and cont...

We consider an infinite-horizon linear-quadratic minimax optimal control problem for stochastic uncertain systems with output measurement. A new description of stochastic uncertainty is introduced using a relative entropy constraint. For the stochastic uncertain system under consideration, a connection between the worst-case control design problem and a specially parametrized risk-sensitive sto...

This paper presents an observer-based discrete variable structure controller for linear multi-variable systems with unmatched additive uncertainties, an extension of the results reported in Tang and Misawa (1998) to the output feedback case. It is shown that the incorporation of a prediction observer with uncertainty estimation into the controller guarantees the attractiveness and invariance of...

Background:Despite some successful dynamic simulation of self-impact double pendulum (SIDP)-as humanoid robots legs or arms- studies, there is limited information available about the control of one leg locomotion.Objective :The main goal of this research is to improve the reliability of the mammalians leg locomotion and building more elaborated models close to the natural movements, by modelin...

Induction motors (IMs) are widely used in many industrial applications due to their robustness, low cost, simplicity and relative good efficiency. One of the major considerations for IMs is their speed control. PI (proportional-integrator) controllers are usually used as speed controller. Adjusting the gain of PI controller is time-consuming which needs thorough considerations. Hence, fuzzy con...

this paper presents a new optimization algorithm to design an optimal proportional, integral, derivative (pid) controller in hydro-turbine generator governor for damping output frequency oscillations. in this research, we utilize a stochastic and optimal based pid controller to control frequency-response of the hydro turbine. the proposed algorithm is employed to design an optimal pid controlle...

in this paper, the unified power flow controller (upfc) is enhanced with a chaotic particle swarm optimization (cpso) damping controller in order to mitigate the low frequency oscillations (lfo) in a single machine infinite bus (smib) power system. the designed damping controller is an optimized lead-lag controller, which extracts the speed deviation of the generator rotor and generates the out...