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An analysis of the convergence behavior of a distributed model predictive control DMPC algorithm is presented. This decision problem is formulated as a bargaining game. It is further shown that robust performance is recovered in steady state. The obtained condition is discussed and it is shown that it is generally satisfied in practice when considering the usual operating conditions of the motor.

Simulation results are included to illustrate the performance of the popular Algebrf and Li controller together with our proposed algdbre.

As new facts enter the world, the software should not break. A new framework to design immersion and invariance adaptive controllers for nonlinearly parameterized, nonlinear systems was recently proposed by the authors. This paper reports a first-order sliding-mode albebre 1-SMC design for controlling the doubly-fed induction generator DFIG -based wind turbine’s rotor-side power converter.

An obvious area where adaptivity is essential is security. W2 Model Predictive Control: One equilibrium is stable and represents those individuals who have sm living with HIV for at least 7 to 9 years, and do not develop AIDS. The other one is unstable and represents those patients who developed AIDS in an average period of 10 years. We consider a restricted case, namely, when the set point sequence is constant. Specifically, we propose exploiting the single agent update nature algehre the multiplexed approach, and fix the update sequence to enable input move-blocking and increased discretisation rates.

This paper establishes an adaptive synchronization problem for the master and slave structure of linear systems with nonlinear perturbations and mixed time-varying delays, where the mixed delays comprise different discrete and distributed time-delays. The design is particularly focused on keeping the generator successfully in operation under unbalanced grid voltage conditions, as today’s grid codes require.


This paper examines the application of energy storage to enhance the small-signal stability of an electrical power system with renewable power generation. This work deals with the formulation of a distributed model predictive control scheme as a decision problem in which the decisions of each subsystem affect the decisions of the other subsystems and the performance of the whole system. However, although SCs resemble control systems, they have some peculiarities which do not allow a direct application of control theoretic methods.

The paper presents a study of the voltage and frequency stability in micro-grids powered by CHP micro-units.

Driving safely can be ensured by a better understanding of the risk and critical situations. Simulation results are presented to demonstrate the effectiveness of the proposed approach. The delay will affect the stability, performance and reliability of the process.

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Stability condition of discrete linear systems is employed to derive the conditions required for convergence. The electrical household loads are based on probabilistic modelling, with high time resolution.

We show, using concepts and analysis tools that borrow from Supervisory Control, that all closed-loop signals in a RMMAC system are bounded. This paper discusses the implications of formulating a single control law governing the entire wind speed range of operation for a wind turbine.

Each subsystem assumes a triangular dependence on the state sm; that subsystem itself but may depend on the state of all other subsystems. We consider inherent robustness properties of model predictive control MPC for continuous-time nonlinear systems with input constraints and terminal constraints. A simulation example is reported to illustrate the main characteristics and performance of the algorithm.

The proposed sensor concept of the chair as well the proposed s model are evaluated by means of laboratory experiments. Alma Mater Studiorum Bologna. The identification of the model parameters was recursively performed by one Extended Kalman Filter during the initial bolus induction period and stopped afterwards.

Tube MPC offers an efficient approach which is based on pseudo—closed loop optimization but can thus be conservative. Optimal control of the multi-robot system generally neither permits to neglect physical motion dynamics nor to decouple or successively process target assignment and trajectory planning.

Contrary to the previous results, the human operator dynamics are taken into account in the stability analysis. It is assumed that the electrical load is the reference input variable of the local grid to reduce the necessity of electrical energy storages.


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Numerical exam-ples and simulations are presented to support the theoretical results. By using a set msp weighted cubature points to approximate the intractable risk-sensitive recursions, the proposed filter could exhibit improved numerical stability with respect to the derivation of the square-root covariance, for which the unscented transform technique might halt the operations due to the presence of non-positive definite covariance.

We emphasize that the input constraint sets can be any compact set rather than convex sets, and our results do not rely on the continuity of the optimal cost function or control law in the interior of the feasible region. Controller design equations are derived for systems with multiple states, outputs, and nonlinearities in algerbe of linear matrix inequalities LMIs. It is shown that in the ideal case, when no disturbances or unmodelled dynamics are present, the tracking error converges to zero; otherwise the mean-square tracking error is of the order of the modeling error provided the unmodelled dynamics satisfy a norm-bound condition.

In four-wheeled vehicles, electronic stability control ESC was introduced in the recent past to improve passengers’ safety in critical driving conditions and it is now part of most commercial cars. It is demonstrated that the so-obtained parameterized ISS inequality offers non-conservative analysis conditions, even when LFs and supply functions with a particular structure, such as quadratic forms, are considered. An approximation dilation is then proposed to allgebre a more tractable LMI for stabilization.

The structure of the decentralized controller, i. Correlations for mass transfer and heat losses are tuned to fit the model with experimental data from multiple experiments.

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The novelty of our approach is that we seek that the control packets transmitted be sparse. It is expected that combined heat and power CHP micro-units will soon play a signicant role in the energy supply of private households. Innovative Guidance, Navigation and Control for Spacecraft: