Non-cooperative intelligent control agents (ICAs) with dedicated cost functions, can lead the system to poor performance and in some cases, closed-loop instability. A robust solution to this challenge is to place the ICAs at the feedback Nash equilibrium point (FNEP) of the differential game between them. This paper introduces the designation of a robust decentralized infinite horizon LQR control system based on the FNEP for a Linear time-invariant system. For this purpose, two control strategies are defined. The first one is a centralized infinite horizon LQR (CIHLQR) problem (i.e. a supervisory problem), and the second one is a decentralized control problem (i.e. an infinite horizon Linear-quadratic differential game). Then, while examining the optimal solution of each of the above strategies on the performance of the other, the necessary and sufficient conditions for the equivalence of the two problems are presented. In the absence of the conditions, by using the least-squares error criterion, an approximated CIHLQR controller is presented. It is shown that the theorems could be extended from a two-agent control system to a multi-agent system. Finally, the results are evaluated using the simulation results of a Two-Area non-reheat power system.

In this paper، the main goal is to reduce the heave motion between a surface effect ship (SES) and a wind turbine in order to safely transfer equipment and person to SES. For this purpose، an LQR control system is designed to damp the vertical motion of the surface effect ship in critical sea states including high-frequency and high amplitude regular waves as well as high frequency irregular waves. The simulation results show the high quality of the system control in the studied sea condition. A comparative analysis of LQR and PID approaches demonstrate the high performance of the new designed control system. The proposed controller outperforms the traditional PD.

Non-Linear characteristic of tire forces is the main cause of vehicle lateral dynamics instability, while direct yaw moment control is an effective method to recover the vehicle stability. In this paper, an optimal Linear quadratic regulator (LQR) controller for roll-yaw dynamics to articulated heavy vehicles is developed. For this purpose, the equations of motion obtained by the MATLAB software are coded and then a control law is introduced by minimizing the local differences between the predicted and the desired responses. The influence of some parameters such as the anti roll bar, change the parameters of the suspension system and track wide in articulated heavy vehicles stability has been studied. The simulation results show that the vehicle stability can be remarkably improved when the optimal Linear controller is applied.

This paper deals with the study and comparison of passive and active landing gear system of the aircraft and dynamic responses due to runway irregularities while the aircraft is taxying. The dynamic load and vibration caused by the unevenness of runway will result in airframe fatigue, discomfort of passengers and the reduction of the pilot’s ability to control the aircraft. One of the objectives of this paper is to obtain a mathematical model for the passive and active landing gears for full aircraft model. The main purpose of current paper is to design Linear quadratic regulator (LQR) for active landing gear system that chooses damping and stiffness performance of suspension system as control object. Sometimes conventional feedback controller may not perform well because of the variation in process dynamics due to nonLinear actuator in active control system, change in environmental conditions and variation in the character of the disturbances. To overcome the above problem, we have designed a controller for a second order system based on Linear quadratic regulator. The performance of active system is compared with the passive landing gear system by numerical simulation. The results of current paper in compared with the previous work mentioned in reference, demonstrates 37.04% improvement in body acceleration, 20% in fuselage displacement and 13.8% in the shock strut travel. The active landing gear system is able to increase the ride comfort and good track holding by reducing the fuselage acceleration and displacement and load induced to airframe caused by runway excitation.

In this paper, two main subjects are dealt with: stabilization of supercavitating vehicles in depth mode and estimating the state variables of the vehicle in order to control the vehicle in this mode. Using the feedback Linearization method, the model of the system is Linearized and a Linear quadratic regulator is designed for the system to stabilize it. This method needs to feedback all states of the system, while measuring all the states is practically infeasible. Then, it is needed to estimate some of the states using the model of the system and the sensor measurements. This is performed here using two well-known filters of EKF and UKF. Through simulations, it is shown that both filters can estimate the states of the system in the depth mode, stabilize the vehicle in this mode and reject the disturbances. It is observed that each filter can estimate some of the states more accurately. In simulations, the performances of the designed controllers are examined, practical issues like actuator saturation are taken into account and the ability of the controllers to stabilize the vehicle is demonstrated.

Sprayers are important tools in agriculture that usually moved on the field by tractor. Sprayers should distribute the constant rate of chemicals during various conditions encountered in the field. Unwanted vibrations of sprayer boom cause redaction of its life time and over doses and under doses of chemical sprayed on the field. Therefore, in this study a model of suspension system for rotational vibrations of sprayer boom is proposed using horizontal and vertical elements of spring and damper. Then, the state space of the dynamical system is derived. In this state space, absolute rotation of the frame connected to the tractor around the horizontal axis (tractor roll) is input and absolute rotation of the sprayer boom around the horizontal axis is output. Also, the optimal gain matrix is designed for the state-space of system using Linear quadratic regulator (LQR). Finally, impulse, step and ramp responses of sprayer boom are calculated and compared to impulse, step and ramp responses of system without controller. The results show that the designed controller significantly reduces rotational vibration of sprayer boom and improves the performance of sprayer.

In this paper Linear quadratic Control (LQR) for 2-D systems is considered .By transferring a 2-D system to 1-D Wave Advanced Model (WAM) the theory available for 1-D LQR problem will be extended to 2-D systems. Then the final results will be held in the initial 2-D system's format. In this case some numerical difficulties will be discussed. As a secondary matter, results will be used for large scale 1-D systems as well.

This study aims to report on the application of Linear quadratic Integral (LQI) based global maximum power point tracker (GMPPT) method for transferring the available maximum power from photovoltaic (PV) systems to load in unshaded and shaded conditions. For the maximum power transmission under varying the environmental conditions and partially shaded conditions, MPPT technologies are utilized in PV systems. For the improvement of functioning MPPT, a new two-level control structure which decreases difficulty in the control process and efficiently deals with the uncertainties in the PV systems is introduced. In the proposed approach, the reference voltage at the global maximum power point (GMPP) is estimated by a new scanning algorithm. The difference between the reference voltage and the voltage of the PV array is then used by LQI controller to generate the duty cycle for a boost converter. The design process of the proposed approach is explained as step by step. The benefits of the approach are quicker tracking capability, transferring maximum deliverable power and simple implementation. To verify the proposed method, several irradiation profiles that create several peaks in the P-V curve are used. The simulation results show that the proposed method causes PV systems to track the GMPP immediately so that no oscillation around the GMPP is observed. Therefore, maximum efficiency can be derived from the PV system.

The main aim of this paper is to find an optimal interval control law for quadratic Linear problems under interval uncertainty. For this purpose, using Bellman's optimality principle and interval Hamilton-Jacobi-Bellman inequalities, the interval optimal control problem is transformed into a system of interval differential inequalities. These inequalities are called Riccati's differential inequalities, which is a result of the dynamic programming method. To solve this system of inequalities, we use inclusion relations and interval arithmetic. By this method, we can obtain the upper and lower bounds of the solutions. We also use Hokuhara's generalized difference to reduce errors in the interval arithmetic. We apply the presented method for solving some interval quadratic Linear optimal control problems by using MATLAB software. The obtained results show the efficiency of the proposed method.