https://www.selleckchem.com/products/t0901317.html This paper concerns with the issues of designing an improved-equivalent-input-disturbance (IEID) based robust two dimensional modified repetitive control (2D MRC) for a class of fuzzy systems in the presence of aperiodic disturbances. Specifically, IEID-estimator is implemented to the 2D MRC systems that estimates all types of disturbances and compensates them for assuring robust stability. In particular, the proposed 2D MRC system has two different type of behaviours such as continuous control and discrete learning independently. To obtain gains of the observer and the controller, an adequate set of robust stability conditions is derived in the form of a linear-matrix-inequalities. Finally, simulation results for three numerical examples are provided to depict the efficacy of the proposed control technique.In this paper, a novel memristive neural networks model is developed. In the new model, the states of memristors are related to the initial resistance of the memristors and the amount of charge flowing through them in a specific direction, which embodies the memory characteristic of memristors. As a consequence, parameters in the model vary continuously and cannot be determined by the states of neurons. Existing results on synchronization of memristive neural networks are useless to this model. To investigate the synchronization of the new model, the main difficulty is how to deal with the time-varying parameter mismatches between the drive and response networks. Since the error is unbounded and only utilizing output feedback control is not enough, a sliding mode controller is designed. An integral sliding surface is designed for the desired sliding motion, and a feasible control law is proposed. Moreover, an example is given to demonstrate the novelty of our model and to illustrate the effectiveness of the sliding mode controller. Skin toxicity is a common adverse effect of breast radiotherapy. We investigated w