This study was conducted during summer and winter of 2018- 2019 in the agricultural research field of Shahid Chamran University. Experimental design was split- plot based on RCBD with three replications. The main plot was the type of agricultural system in three levels including conventional (Conv), organic (Org) and sustainable (Sust) (integrated between Conv and Org) and sup- plot was the type of pre- cultivated crop in sequence with wheat including cultivation of mung bean (M- W), corn (C- W), sesame (S- W) and fallow (F- W). Yield quantity (yield and its component) and quality (grain protein), an estimate of photosynthesis matter transfer index of wheat and soil organic carbon (SOC) after one double-cropping were measured. The result showed that the highest (545.04 g/m2) and the lowest (409.28 g/m2) seed yields were obtained in Conv and Org respectively. In contract, with the changing type of system from Conv to Org, grain protein was increased significantly (from 8.3 to 9.6 %). In addition, the highest (535.47 g/m2) yield of wheat was obtained from M- W double cropping. On the other hands the highest remobilization and current photosynthesis matter were obtained in the organic agricultural system with M- W and conventional with M- W double cropping. The situation of SOC showed that the highest (33.18 mg/g) SOC was obtained in the organic agricultural system with C- W double cropping. The reason for improving SOC in the organic and sustainable agricultural system was application of organic matter (compost and vermicompost) and crop residue management. Totally, from the crop ecology point of view, sustainable agricultural method with a sequence of M- W was the most desirable system.

In this paper&lrm, , &rlm, &lrm, we use the least squares method to solve LR fuzzy interval systems by transforming an interval fuzzy number into two triangular fuzzy numbers. Then, &lrm, w&lrm, e reduce the distance between the two obtained triangular fuzzy numbers to solve the fuzzy &lrm, LR&lrm, interval linear system. Essentially, we convert an LR fuzzy interval linear system into a triangular fuzzy linear system and subsequently solve it using the least squares method introduced &lrm, in [17, 18].

In this work, we propose a simple method for obtaining the algebraic solution of a complex interval linear system where coe cient matrix is a complex matrix and the right-hand-side vector is a complex interval vector. We  rst use a complex interval version of the Doolittle decomposition method and then we restrict the Doolittle's solution, by complex limiting factors, to achieve a complex interval vector that satis es the mentioned system.

The aim of this paper is to propose a novel method for controlling a class of parameter-varying systems by controlling interval observer. The interval observers, that are applicable for the systems with uncertainty, estimate bounds on the states instead of estimating the states. It has been shown that by designing appropriate control inputs for controlling the bounds of the interval observer, the states of the system can be also controlled using the same control inputs. For this purpose, a suitable interval observer is firstly designed for the parameter-varying system and the required conditions, for which the dynamical system consisting of lower and upper bounds on error is monotone, are presented. Then, a novel controller is designed for stabilizing the interval observer such that the bounds on the states are stabilized and thereby the states are also stabilized. The proposed controller is based on adaptive sliding mode control method that is utilized to tackle the effects of variations in some parameters of the interval observers as well as the existing disturbances in the system. By choosing an appropriate Lyapunov function, the conditions and areas for the stability of the observer are determined. Simulation results, obtained by applying the method to a sample system, show the effectiveness of the proposed method.

This paper is concerned with the problem of delay-dependent passive analysis and control for interval stochastic time-delay systems. The system matrices are assumed to be uncertain within given intervals, the time delay is a time-varying continuous function belonging to a given range, and the stochastic perturbation is in the form of a Brownian motion. By using ItO's differential formula and the Lyapunov stability theory, delay-dependent stochastic passive control criteria are proposed without ignoring any useful terms by considering the information of the lower bound and upper bound for the time delay. Based on the criteria obtained, a delay-dependent passive controller that ensures the stochastic passivity of the closed-loop system is presented. Then, the controller gain is characterized in terms of LMIs, which can be easily checked by resorting to available software packages. Numerical examples are given to demonstrate the effectiveness of the method.

In this study the possibility of using fuzzy inference system efficiency, creating a bridge between meteorological, plant parameters, and Daily Yield, and comparing the accuracy of Daily Yield using these systems were investigated. After analyzing the different models and different combinations of daily meteorological data, seven models for estimating daily Yield were presented. For these models, the calculated Yield from AQUACROP model was considered as a base and the efficiency of other models was evluated using statistical methods such as root mean squared error, error of the mean deviation, coefficient of determination, Jacovides (t) and Sabbagh et al. (R2/t) criteria. An experiment was carried out during the 2014-2015 growing season in the Agricultural Research and Education Center of Khorasane Razavi province using a randomized complete block design with a split plot arrangement and four replications. This experiment was including of three irrigation levels treatments as the main plot and three method of planting treatments (transplanting 20-days, transplanting 30-days and direct seeded) as subplots. From the available data, 75 percent was used for training the model and the rest of 25 percent was utilized for the testing purposes. The results derived from the fuzzy models with different input parameters as compared with AQUACROP model showed that fuzzy systems were very well able to estimate the daily Yield. Fuzzy model so that the highest correlation with the 9 input variables (r=0. 98) had in mind and evaluate other parameters, the model with 2 parameters, match very well with the AQUACROP model had stage training. In the test phase, training phase was very similar results and the model with the second phase of harvest index and canopy cover will get the best match. According to the results of this study it can be concluded that fuzzy model approach is an appropriate method to estimate the daily yield.

This paper investigates the stabilization problem of an autonomous Linear Time Invariant (LTI) switched system with interval uncertainty and unstable subsystems. It is proved that the system would be stable by using a common Lyapanov function whose derivative is negative and bounded by a quadratic function within activation regions of each subsystem. First, a sufficient condition for the stability of an LTI switched system with interval uncertainty, based on the convex analysis and interval set theoretical approach, is presented and proved. Moreover, conservatism in the stability robustness bound is obtained. Then, a switching control law is designed to shift the LTI switched system among subsystems to ensure the decrease of the Lyapanov function within the state space. Finally, in order to decrease the switching frequency and to avoid chattering, the switching law is modified. Two examples are included to demonstrate the effectiveness of the theoretical findings.

A discrete event system (DES) is a dynamic system that evolves in accordance with the abrupt occurrence, at possibly unknown irregular intervals, of physical events. Because of the special nature of these systems, different tools are currently used for their analysis, design and modeling. The main focus of this paper is the presentation of a new modeling approach of Discrete Event Systems. The proposed approach is based on hybrid model which combines Interval Constrained Petri Nets (ICPN) and Timed Automata. These tools allow us to evaluate, respectively, the quality variations and to manage the flow type disturbance. An example analysis illustrates our approach.