In this work, a discrete second order sliding mode control with a new sliding function for a linear uncertain system with state delay is proposed. The systems are assumed to have structured mismatched time varying uncertainties. Firstly, a new sliding function include a present and a past value of the state, called dynamic surface, is designed by means of linear matrix inequalities (LMI). Then, a robust discrete second order sliding mode controller with this new function is investigated to overcome the effect of time delay and uncertainties in the closed loop. A numerical example illustrates the effectiveness and the advantages of the proposed approach.

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The control of time delay systems is still an open area for research. This paper proposes an enhanced model predictive discrete-time sliding mode control with a new sliding function for a linear system with state delay. Firstly, a new sliding function including a present value and a past value of the state, called dynamic surface, is designed by means of linear matrix inequalities (LMIs). Then, using this dynamic function and the rolling optimization method in the predictive control strategy, a discrete predictive sliding mode controller is synthesized. This new strategy is proposed to eliminate the undesirable effect of the delay term in the closed loop system. Also, the designed control strategy is more robust, and has a chattering reduction property and a faster convergence of the system s state. Finally, a numerical example is given to illustrate the effectiveness of the proposed control.

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Distributed generation (DG) has become increasingly popular in many power systems across the world. It is an effective approach to facilitate the usage of renewable resources for power generation purpose. However, the installation of DGs in a power system may change the pattern of the power flow and cause various complexities in the system. How to plan DGs to best utilize renewable energy source while maintaining system security is an important problem. In this paper, an eigenvalue based analysis method is proposed for DG location planning with detailed case studies.