model predictive controller is widely used in industrial plants. uncertainty is one of the critical issues in real systems. in this paper, the direct adaptive simplified model predictive control (smpc) is proposed for unknown or time varying plants with uncertainties. by estimating the plant step response in each sample, the controller is designed and the controller coefficients are directly ca...

this study was carried out to control johne’s disease (jd) without interfering with tuberculosis (tb)control programme. a dairy herd (n>1500 heads) was used over a period of 6 years, from 1994 to 1999 forthis investigation. the herd had a history of heavy infection with mycobacterium avium paratuberculosis(map) with culling rates of 1.5 and 5%, in 1991 and 1995, respectively. the mean annual lo...

in this research, a new control policy for the acceptance sampling problem is introduced. decision is made based on the number of defectives items in an inspected batch. the objective of the model is to find a constant control level that minimizes the total costs, including the cost of rejecting the batch, the cost of inspection and the cost of defective items. the optimization is performed by ...

although control charts are very common to monitoring process changes, they usually do not indicate the real time of the changes. identifying the real time of the process changes is known as change-point estimation problem. there are a number of change point models in the literature however most of the existing approaches are dedicated to normal processes. in this paper we propose a novel appro...

in the face of limited water resources, better utilization and operation of irrigation networks is essential. use of control systems is considered as one of the most assured ways to achieve the aim. in the course of the present study, two centralized controllers are applied to the west canal of aghili irrigation district in i. r. iran. the proposed control algorithms consist of a distant downst...

this paper proposes a discrete-time repetitive optimal control of electrically driven robotic manipulators using an uncertainty estimator. the proposed control method can be used for performing repetitive motion, which covers many industrial applications of robotic manipulators. this kind of control law is in the class of torque-based control in which the joint torques are generated by permanen...

nuclear power reactors are, in nature nonlinear and time varying. these characteristics must be considered, if large power variations occur in their working regime. in this paper a robust optimal gain scheduling controller for regulating the power of a nuclear reactor has been designed and simulated. the proposed controller is capable of regulating power levels in a wide power range (10% to 100...

in this paper, first the available single charting methods, which have been proposed to detect simultaneous shifts in a single process mean and variance, are reviewed. then, by designing proper simulation studies these methods are evaluated in terms of in-control and out-ofcontrol average run length criteria (arl). the results of these simulation experiments show that the ewma and ewms methods ...