The body freedom flutter phenomenon is one of the aeroelastic instabilities that occurs due to the coupling of the aeroelastic bending mode of the wing with the short-period mode in the flight dynamics of the aircraft. By using the aeroservoelastic model and applying closed loop control, this phenomenon can be suppressed in the operating conditions of the aircraft and the velocity of this event can be increased. The simplest model aircraft capable of displaying this instability includes the flexible wing and the planar flight dynamics model. For this purpose, the wing structure is modeled using the Euler-Bernoulli beam and, the theory of minimum variable state is used to model unstable aerodynamics to make the conditions suitable for modeling the system in state space. In the control section, the elevator is used as the control surface and LQR theory with Kalman filter is used to body freedom flutter suppression. Finally, the effect of adding a closed loop control to increase the body freedom flutter velocity and the limitations of this work are studied.

In this work, nonlinear model of a Heating, Ventilating, and Air Conditioning (HVAC) system in the cooling mode is first derived using energy and mass balance equations. All components of the system are independently modeled in the modeling process. The responses of the open loop system are then obtained and the reliability of modeling is verified by comparing the actual system records with those of the other researchers. The nonlinear model of the system is linearized using the Jacobian matrix method, and a PID-action as well as the Linear Quadratic Regulator (LQR) controller as the linear control systems are developed on the linear model. PID-action is a classic and robust controller and the LQR is a modern and optimal controller system. In the final part, Sliding Mode Controller (SMC) is designed on the nonlinear model as a robust and proper controller system. The comparison between these proposed controller systems confirms the superiority of the SMC controller, which results in a reduction of the settling time, the omission of overshoot, and an improvement in the actuator's performance via the reduction of energy consumption in the system.

In this paper, dynamical modeling of a gyro stabilized platform in the presence of angular motions of the vehicle is studied. After introducing the computational models, the system is simulated first in an uncontrolled and then in closed loop mode using PID & LQR controllers, separately. Results show that both PID & LQR controllers have good capability to stabilize the gyro stabilized platform and can provide a fast and over damped process for it.

Nowadays, the Doubly-Fed Induction Generators (DFIGs) based Wind Turbines (WTs) are the dominant types of WTs connected to grid. Traditionally the back-to-back converters are used to control the DFIGs. In this paper, an Indirect Matrix Converter (IMC) is proposed to control the generator. Compared with back-to-back converters, IMCs have numerous advantages such as: higher level of robustness, reliability, reduced size and weight due to the absence of the bulky electrolytic capacitor. According to the recent grid codes it is required that the wind turbines remain connected to the grid during the grid faults and the following voltage dips. This feature is called Low Voltage Ride-Through (LVRT) capability. In this paper, the Linear Quadratic Regulator (LQR) controller is used for optimal control of the DFIG. The weighting matrices of the LQR are obtained by using the Genetic Algorithm (GA) technique. With the LQR controller the intention is to improve the LVRT capability of the DFIG wind turbines to satisfy the new LVRT requirements.Compared to the PI controller, the superiority of the LQR controller in improving the transient stability and LVRT performance of the DFIG wind turbines is shown. Simulation results confirm the efficiency of the proposed controller.

The paper compares the performance of two altitude controllers, model predictive controller (MPC) and linear quadratic requlator (LQR), for aircraft in cruise flight and height change conditions. The design of the controllers is based on the linearized state space matrix of the aircraft’s longitudinal motion around the trim conditions. The controllers’ ability to track the desired altitude while satisfying input and state constraints is evaluated, and it is found that both controllers are effective in maintaining the desired height. However, the MPC controller performs less overshoot, settling time and transient error than the LQR controller and achieves a more efficient control input by predicting the future behavior of the system. The proposed altitude controllers provide a promising solution for maintaining the desired aircraft altitude in cruise flight conditions, and the comparative analysis of the two control methods can assist in selecting the appropriate control strategy for a given aircraft system based on the desired performance requirements.