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.

Due to the importance of fault detection in maintaining the performance and immunity of control process, various methods have been proposed where as well as fault detection, the robustness of the system with respect to uncertainty and disturbance has been also discussed. In this regard a compromise between error sesitivity of the system and its robustness should be considered. One of the proposed methods is based on transformation of robust fault detection problem to a standard H¥ model-matching one. In this paper after the selection of a proper reference model for the robust fault detection problem, a residual generator will be considered on the basis of an H¥ minimization of the difference between reference model the realastic residual generator using LMI technics. A design example has been chosen to demonstrate the effectiveness of the proposed approach.

In this article, a novel observer has been designed for the online estimation of time delay in SISO-LTI continuous time SYSTEMS with uncertain and time variant delay in the control input. It is obvious that Laplace transfer function of a delayed system includes a time delay factor. In this paper, it is assumed that the only uncertain and time variant parameter in the system is the very system’ s time delay parameter. The main idea used in designing the proposed observer is based on the establishment of duality principle between controller and observer, such that a direct adaptive controller structure (MRAS) is indirectly used for designing an estimator. For this, the main sections in an MRAS control system are organized the way that designing the controller will lead to designing the delay estimator in dual problem. In fact, adaptation rule in designing the controller will express the same estimator mechanism in the dual problem. Also, in computing the estimation mechanism, the two methods, one based on Lyapunov Theory and the other based on MIT rule, are used. Eventually, simulation results are indicative of the rather desirable performance of the proposed estimator in dealing with uncertain and time varying delays.

Three methods are discussed for stabilizing Linear Predictive Controller: Infinite Horizon Control (based on Optimal Control), Finite Horizon Control with end-point constraint, and in the third approach, at first the process is stabilized and then controller is designed. In this paper, a new method based on Finite Horizon Control with end-point constraint is proposed; it enables us to control some processes with repetitive unstable pole (Minimum or Non-minimum phase) that can’t be stabilized with existing methods. In these processes, step response has a variety range and the dynamic matrix for long prediction horizon is singular and then existing method fails to have a stable process. We modify the cost function of GPC Controller by adding terms to penalize error variations as well error and adjust these parameters. We have examined the method described for a practical system (Stewart Platform) with 6 unstable poles and 5 unstable zeros.

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.

The present study presents an adaptive controller for LTI SYSTEMS with an unknown and time-variant input time delay with the purpose of tracking. Due to the wide area considered for time delay variations, the structure of the proposed controller is considered to be in the form of MuLTIple Adaptive Control (MAC). The presented adaptive control system is of indirect type, i. e., at any moment, one band of time delay is first identified using a proposed estimator, and then the main control signal, which is a linear combination of muLTIple controllers output, is formed with a switching rule in the supervisory subdivision. In fact, each muLTIple controller in the MAC structure with fit weights participates in forming the main control signal. The muLTIple controllers used in this study are of PID type. It should be noted that the parameters for the individual muLTIple controllers, for the system under control, are adjusted offline and proportional to its corresponding time-delay sub-band using a genetic algorithm. Finally, simulation results show the relatively desirable performance of the proposed control system and observer in facing with wide unknown and time-variant delays.

In this paper, an open-loop control scheme is developed to design of a dead-beat control effort in the high order continuous-time LTI SYSTEMS. The dead-beat control is really a finite-time control law. In this method, the input signal is manually selected such that the output signal becomes constant in a finite time. In the LTI SYSTEMS, having known the step response, a control signal could be exactly selected such a way that the control objective would be met in a finite time. For this goal, the dead-beat control problem is firstly investigated in a standard first order system. Then a similar problem is studied in the second order SYSTEMS. Finally a general design framework would be developed to obtain a dead-beat control policy in the high order continuous-time SYSTEMS. In the proposed method, the control design problem is deliberately converted into the solution of a linear matrix equation. Therefore the control signal would be determined via the solution of an algebraic equation. The suggested procedure has been successfully applied in some continuous-time LTI SYSTEMS. The simulation results show the effectiveness of the proposed control method for designing of a finite-time control law in the continuous-time LTI SYSTEMS.

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.

In statistical process control, one objective is to control the stability of a process. A process is stable when its mean is in control and variance bounded. Di, erent control charts were introduced for monitoring the mean and variance of a process by plotting suitable test statistics on the chart. In this research, design of a system which converts the sample mean into test statistics was proposed. The second-order , lter, a special class of the Linear Time Invariant (LTI) SYSTEMS, was used to design the converting system. It was shown that design of a low-pass , lter was better for detecting a level (mean) change in the process. Markov chain approach was also employed to construct an appropriate control chart and to estimate its control limits. Simulated data under normality assumption for di, erent scenarios were used to compare the proposed control chart with Shewhart and Exponentially Weighted Moving Average charts by means of Average Run Length (ARL) and Percentage of False Signals (PFS) criteria. Existing data from the Central Bank of Iran was also applied to evaluate the suggested method. The signal-to-noise ratio was used to assess the performance of this method at di, erent stages. Results indicate that the proposed method detects shifts more rapidly.