Saving energy in various sections of the building and improving productivity in the face of energy crisis and environmental pollution can be one of the main challenges in the world and our country. In this paper, based on the necessity of controlling and minimizing energy consumption by considering the maximum optimal temperature conditions in different areas of the building, a control method based on the predictive controller is used, which takes into account the effects of the time of use for sources. The predictive controller predicts the optimal control input for future moments according to the definition of the cost function based on the ambient temperature error and the weighted expression of the control input. In this paper, the issue of optimization is thoroughly studied, evaluated, and simulated. The temperature change model in buildings and the proposed control scheme are implemented in MATLAB software and the system is simulated using the building environment. The simulation is performed under several different scenarios of time of use and conditions to show the performance of the proposed design. Based on the results of the proposed control method, the accuracy and performance of the model in different scenarios of building conditions are acceptable. Manuscript profile

This paper was dealt with the optimization of energy for tracking the magnetic levitation ball by using the technique of State-Dependent Riccati Equation. The magnetic levitation ball is widely used in various fields. This system includes a steel ball suspended by electromagnetic force. The differential equations of this system are nonlinear. Generally, first, these nonlinear equations are linearized around an equilibrium point. Then, a Linear Quadratic Tracker controller is designed for this system. Note that this system has a non-zero equilibrium point. However, in the technique of State-Dependent Riccati Equation, the nonlinear equations are linearized by using the method of State-Dependent Coefficients. If the system is pointwise stabilizable and detectable, the State-Dependent Riccati Equation has an answer. Then, an optimal control law is extracted so that the energy of tracking is minimized. In the end, it has been shown that four different trajectories are tracked appropriately using the proposed method. Manuscript profile

today, the use of different types of industrial robots is developing due to the growth of technology and the expansion of research in design and control. Industrial robots are a fundamental component of most modern automation systems. In this paper, we study the dynamic modeling and adaptive control of flexible joint robots (FJR). In this regard, the dynamic model of the robot will be extracted in state space using the Lagrange-Euler method. A new adaptive backstepping control approach is introduced to control FJR motions and improve the adaption and robustness of the nonlinear system. By using this method, variations of the model parameters will not affect the robust performance of the proposed controller. To evaluate the proposed method, MATLAB software is used to simulate a 2-joints FJR model with an adaptive backstepping controller. Based on results the proposed method controls the model property without overshoot, by considering the saturation limit of input control. Manuscript profile

Abstract - Based on the study of the theoretical foundations of the research, it is determined that so far there is no detailed study on heating and cooling energy related to zero-energy buildings in the recent research based on energy waste in buildings. Therefore, in this article, by simulating commercial buildings and simulating the correct materials and strategies in the heating and cooling system, as well as investigating the insulation of buildings, we will study the effect of zero-energy building materials on energy wastage to model the temperature variations in building and control to achieve desire value. This article, taking into account the effects of heat transfer through building walls, the energy consumption model, and by genetic algorithm model predictive control (MPC) method optimizes the indoor temperature of the building. For this purpose, the genetic algorithm is used to determine the best control input in the form of building heating. The simulation of this process has been done in MATLAB software and the method of modeling heat loss and temperature change outputs shows that the proposed method has a good performance. The maximum of overshoot of the temperature is %4 and the cost function of GA algorithm is 165 based of minimum control effort and temperature error. Manuscript profile

In this article, we investigate different control methods and control input disturbance removal in the two-link flexible robot. For this purpose, we use the linear feedback control method to control the trajectory tracking of the robot's angle with a nonlinear model by reducing the effects of disturbances in the control signal. The main contribiution of this paper is disturbance rejection that effect on performance of robot. In the end, by analyzing and comparing the obtained results, the best method is selected to control and eliminate the control input disturbance in the flexible two-link robot. To analyze the results of this research, MATLAB software and the system simulation are performed and according to the desired trajectory for the robot arms, the optimum control input for the system is obtained. Based on the results, the proposed control structure controls the model property without overshooting and by considering the saturation limit of input control. Manuscript profile

One of the most important human needs is fresh water. Production of electricity and fresh water in compliance with environmental issues is a very important issue. In the present work, a solar cogeneration system is proposed for the production of electricity and fresh water. Power system and humidifier-dehumidifier (HDH) units are responsible for electricity and freshwater production, respectively. Firstly, thermodynamic analysis is performed to determine the mass, pressure, temperature and other thermodynamic properties of each flow. An economic analysis is then performed to determine the maximum benefit of the system. The results show that the maximum values for profit and net power are 1164 $/h and 20468 kW at pressure ratio 6 and 7, respectively. The mass flow rate of fresh water increases 46.4% when mass ratio of water to air goes up from 1.0 to 1.7 at an inlet hot air dry bulb temperature of 83 ℃. Manuscript profile