جستجوی مقالات مرتبط با کلیدواژه « کنترل تطبیقی » در نشریات گروه « مکانیک »

In this investigation, using the fractional calculus, a controller for trajectory control of a quadrotor is designed. As a matter of fact, one of the most important challenges in quadrotors is changing the mass of the quadrotor for carrying loads. In this paper, the controller is designed adaptive to show appropriate response in the presence of changing mass. For designing this controller, the sliding mode controller is utilized, which the sliding surfaces are considered as a fractional model. The results of this study demonstrate the effectiveness of the fractional-order controller for trajectory control of a quadrotor with changing the mass parameter. Moreover, simulations illustrate that by changing the fractional-order a new controller can be designed which can do the same mission with less control effort. Therefore, utilizing the fractional controller, the Dynamic Load Carrying Capacity (DLCC) of a quadrotor can be increased. The results show that by considering fractional-order = 0.275, the DLCC is maximized. The innovation of this work is the investigation of fractional order controllers in determining the DLCC, which shows that by setting a certain value, the DLCC can be increased by about two times compared to the classical sliding mode control.

Nowadays, industrial systems deal with a wide range of constraints. Input saturation and lack of system model are two types of these constraints. In this paper, a separate model free adaptive data-driven controller for a nonlinear system called a simulator with the conventional configuration of a main single-tailed propeller, twin rotor MIMO system (TRMS) in the presence of input saturation is presented. In the proposed controller, the design of the control input signal only depends on the input and output data of the system and the system model is not used. The purpose of this paper is to control the horizontal and vertical angles of the TRMS system. For this purpose, at first, using the model of TRMS that has been presented for this system in previous articles, a model of the relevant system is expressed and then only using the input and output data obtained from that model, control the defined angles with a separate model free adaptive data-driven control method. Finally, the performed simulations demonstrate the effectiveness of the proposed method for the TRMS, by using two difference reference signals named variable steps and sinusoidal.

Any defect in the flight control system may cause an irreparable problem. Typically, a highly reliable system with human decision-making power is used to prevent or correct such errors in a flying vehicle. A fault tolerant control system is designed to deal with various types of errors that may occur in the system. Fault-tolerant control systems are divided into two main parts. The first part is the error detection and isolation phase and the second part is the control system design phase to overcome the error effects in the system, depending on the type of error and the location of the error, whether the sensor, actuator, or components, the control system must be able to eliminate error effects. In this paper, a neural-adaptive observer is used in the error detection stage, and in the second stage, a control system is designed based on the back-stepping algorithm. Nonlinear six-degree-of-freedom simulation results for an F-18 aircraft model indicate its suitable efficiency in the detection and compensation of fault effects.

In this paper, a model-independent adaptive sliding mode control method based on time-delay estimation (TDE) for a three degrees of freedom (3-DOF) helicopter in the presence of external disturbances and types of uncertainties is presented. In this approach, the switching gain of sliding mode is determined adaptively in order to increase the efficiency in tracking the reference path and reduce the chattering. In the adaptation law which causes rapid convergence to the sliding surface, a small and arbitrary neighborhood of sliding mode polynomials is used. In this neighborhood, it is considered that the derivatives of the adaptive gain are inversely proportional to the sliding variables. In this approach, to avoid using the dynamic model that is accompanied by modeling error, the time delay estimation approach has been used. In the time delay estimation, creating a time delay signal eliminates system dynamics and uncertainties. The uniformly ultimately bounded (UUB) stability of the closed-loop system is also shown. Finally, the efficiency of the proposed approach is investigated by studying the simulation on a 3-DOF helicopter.

Several novel control techniques have been created as a result of the diversity of researches which are conducted about the problem of satellite attitude control. There are always uncertainties in the problem of satellite attitude control in the space missions. Therefore, Adaptive control is a method which is taken into consideration. High computational volume is one of the problems of adaptive control technique. In this paper, a control technique which is based on optimization concepts is introduced for the problem of satellite angular velocity and attitude control. Also, it's developed based on the three-dimensional special orthogonal group, and it's not faced by a singularity problem. For comparison, the linear quadratic regulator (LQR) control technique is simulated. Finally, the results of the simulations show that the performance of the presented adaptive control technique is optimal, and this method is robust to inertia changes.

The effect of climatic and climatic changes in different geographical areas on the types of plants, animals and objects and the importance of protecting the items has led to the study of ideas related to control of air variables in desired conditions. All of the ideas studied in this field lead to the separation of under the control area in order to reduce the effect of the environment on the control variables. This area is then modeled as a system with a defined energy and mass exchange with the environment. In the present study, thermal modeling, dynamic modeling, and control of the variables of a museum which is considered an enclosed area have been investigated. For dynamic modeling, the one-dimensional heat transfer method is used for area elements (DETECt 2.3.1 method). After dynamic modeling, temperature and humidity control have been done using model-reference and modified adaptive methods. Numerical simulation results include the behavior of the system with and without using the controller, the variation of the dynamic variables, and changes in the control signal and the adaptive gains. The results show the success of control methods in the control of temperature and humidity of the studied area.

Disturbance and bounded uncertainty are the most important factors which can be degrade efficient performance of the lower limb exoskeleton. While sliding mode control is a robust control approach against such disturbances, however, by applying the boundary layer in spite of chattering phenomenon, robust performance becomes feeble. In order to overcome this drawback, high order sliding mode algorithms like supper twisting has been proposed in which, chattering phenomenon is mitigated by eliminating the boundary layer. In this paper, an adaptive supper twisting sliding mode control is proposed for a lower limb exoskeleton robot in which the sliding variable and its derivative tend to zero continuously in presence of the disturbance and bounded uncertainty. In addition, the desired trajectory of the upper limb is determined so that in each moment the stability of the robot is guaranteed based on zero momentum point criterion. To achieve maximum stability and minimum error in tracking of the desired trajectories, the controller parameters and the upper limb desired trajectory parameters are optimized using the Harmony Search algorithm. Robot is modeled in ADAMS and then control inputs are applied to the Adams model. Finally, Performance of two controllers is compared. Simulation results reveal the performance of the proposed controller is better than the optimal sliding mode controller.

In this paper, after presenting a brief introduction about Amirkabir University of Technology’s attitude simulator, governing equations are obtained. Viscous friction model is chosen to model the existing friction in the bearings of the attitude simulator. The main purpose of this paper is to design an adaptive attitude control algorithm for the attitude simulator in order to control it in the desired path and estimate the coefficients of friction due to simulator’s bearings. In order to prevent singularity in simulations, Rodriguez parameters are used for kinematics representation. Firstly, the governing equations are transformed into a robotic form. The moments of inertia and coefficients of viscous friction model are assumed as uncertainties. Then, by introducing a Lyapunov function, the stability of the system is checked and the parameters are estimated. The adaptation law is obtained by the Lyapunov function and the stability of the system is then proved. In order to demonstrate the efficiency of this adaptive control algorithm, a nonlinear Lyapunov-based attitude control algorithm is designed and compared to the adaptive controller. The simulations are done in Matlab software package and the parameters of the moment of inertia matrix and coefficients of viscous friction model are estimated by the adaptation law of the controller. During the simulation, the rotational velocity of the reaction wheels are obtained and it is shown that this attitude control algorithm is implementable on the attitude simulator.

Applications of autonomous robots in engineering systems are growing today. Control of an autonomous robot is one of the main problems in this field. Parameters of this type of systems are variable and lead to a time-varying dynamics. A time-invariant controller due to the actual conditions and varying parameters of the system will not result in appropriate responses. On the other hand, real system dynamics is subjected to unpredictable uncertainties and disturbances due to environmental conditions. Therefore, utilized control algorithms should be robust against these effects. In this paper modeling and model-based robust adaptive control of an autonomous robot have been considered. Control of an autonomous system due to the large sensitivity and system specific conditions should be accomplished using particular control algorithms. These conditions have been analyzed for this system. Sliding mode control with system parameters identification as an appropriate control algorithm which contains such conditions has been designed and employed for the control of the system with time-varing parameters. Therefore, first system dynamic model has been obtained. Next, robust adaptive control algorithm has been designed and applied to the system. Obtained results show the effectiveness of the proposed method

In the present article, a real mass-spring system under external excitation with time-varying frequency is studied. The external excitation causes additional oscillations in the real mass-spring system response which disrupt the path tracking procedure. Adaptive control law, which is considered for annihilating the additional oscillations, is equal to a virtual vibration absorber which its stiffness regardless of the real system and external excitation uncertainties, can be updated based on the linear absorber theory until the natural frequency of the absorber reaches the excitation frequency. The variation of the frequency is based on the step and ramp function which relatively are equal to the sudden and transient change from the initial value to the final value of the frequency. Besides, the effects of the noise with various amplitudes existed in the transient variation of the frequency on updating the virtual absorber stiffness is developed. Simulation results are presented to demonstrate that the determined adaptation law guarantees the adaptation of virtual absorber stiffness considering excitation frequency variation based on both step function and ramp function and eliminates additional vibrations of the real system.

This paper investigates the Tri-Tilt Rotor VTOL UAV. The aim of this study is to represent a comprehensive dynamic model, eleven degree of freedom at six flight phases (hover, descend, climb, forward, transient and cruise) and control the vehicle to reach best flight condition. For this purpose, the vehicle equations of motion are derived in tensor form and have been expanded in the coordinate systems, based on multi-body (vehicle and three electric motors) modeling approach in order to consideration of motors gyroscope effects on flight dynamic. Depending on vehicle flight phase, propulsion and aerodynamic forces and moments are determined separately. Blade Element Momentum Theory (BEMT) is used to obtain motors propulsion forces and moments at hover, descend, climb and forward phases. After that, with utilizing of controller for each channel flight, the trim condition is calculated and then for the sake of linearization using analytical method, dynamic and control matrixes are derived. This calculated model is qualified as linear model in order to design the model predictive and adaptive controller. For climb phase, as the nonlinear model receding from linear model, the linear model predictive controller performance was diminishing whereas the function of model reference adaptive control in spite of the uncertainties was better.

In this article, the transfer function of a servo hydraulic fatigue testing machine for composite material specimen is identified based on gray box technique. The system uncertainty is determined by means of the identified linear model. A Feedback and forward robust controller and an adaptive controller based on gain scheduling technique are designed to adjust the closed loop gain for minimizing the error between the amplitude of the reference signals and outputs. Using frequency response analysis of the closed loop system, the control system can compensate low frequency uncertainty up to 10 rad/sec. The experim ental results for block loading fatigue tests, confirms the robust performance of the proposed control system.

This paper presents a control augmentation system (CAS) based on the dynamic inversion (DI) and neural networks for a highly maneuverable aircraft. A neural flight control system is used to provide adaptive flight control, without requiring gain-scheduling or system identification. Neural networks on-line is used to compensate for inversion error which arise from imperfect modeling, approximate inversion, or sudden change in aircraft dynamics. A stable weights adjustment rule for the on-line neural network is derived by the Lyapunov stability theorem. Finally, nonlinear six-degree-of-freedom simulation results for an F-18 aircraft model are presented to demonstrate the effectiveness of the proposed CAS.

The process of failure due to oscillating forces is referred as fatigue, which is the main cause of mechanical failures. Experimental research in this area for validation of theoretical results requires a tension-compression fatigue testing machine equipped with special capabilities. The organized control of force plays an important role in the validity of test results and is an essential part of fatigue testing machines. The main aim of this paper is to enhance the control unit of servo-hydraulic fatigue testing machines in order to reduce settling time. The most important issue is uncertainties in the measurement of the specimen’s stiffness. In this study, the parameters related to mathematical model of fatigue testing machines are detected and the proportional-integral controller is designed and implemented. The obtained results of implementation of this controller shows that the settling time related to the fatigue testing of parts with low stiffness is more than what is expected. Thus, an adaptive controller is proposed and implemented in order to reduce the settling time. So as to obtain more appropriate response to disturbance, the proposed algorithm is combined with the proportional-integral controller. Using this novel controller decreases settling time by 25 % and makes the system response to measurement noise and disturbance more desirable.

In this paper, design of an adaptive controller, as a combination of feedback linearization technique and Lyapunov stability theory, is presented for a parallel robot. Considering a three degree-of-freedom parallel mechanism of the robot, which serves pure translational motion for its end-effector, kinematic and constraint equations are derived. Then the dynamic model of the constrained system is extracted via Lagrange’s method to be used in the robot control. Two optimized trajectories are designed for the end-effector in the presence of some obstacles using harmony search algorithm to be tracked by the robot. An objective function is defined based on achieving to the shortest path and also avoiding collisions to the obstacles keeping a marginal distance from each. The first trajectory is a 2D path with four circular obstacles and the second is a 3D path with three spherical obstacles. Performance of the designed controller is simulated and studied in conditions including external disturbances and varying system parameters. The results show that the proposed adaptive controller has a suitable performance in control of the end-effector to track the designed trajectories in spite of external disturbances and also uncertainty and variation of the model parameters.

Important issues in designing a controller for re-entry vehicles is environmental uncertainties such as rapid changes in atmospheric properties which is an explicit function of altitude and also uncertainties of itselfvehicle such as aerodynamic coefficient, moment of inertia and so on. This paper deals with the design of a control in order to overcome the uncertainty thatuses bank angle as a trajectory control variable.Another issue raised in recent studies has been integration of adaptive controller with guidance systems of re entry vehicles because in real re-entry vehicle the bank angle is not a predefined profile function of velocity or altitude buta guidance algorithm are usedto produce bank commands during the atmospheric flight. Hence, other objectives of the thesis is to study and implementing of a guidance algorithm and proving of desired performance of the designed controller in a perfect scenariofrom starting point of the re-entry path until the opening of parachutes. Performance of designed controller is studied through simulations ofsix degrees of freedom of re-entry vehicle.. The results showed good performance in the presence of parametric uncertainty andunknown initial condition.

The wind turbine blades are made of composite materials and subjected to severe operational loadings. The complexity of composite materials behavior along with variable amplitude loadings dictates the need for experimental setups which can conduct real part test as close as possible to in service loadings. In this regard, wind turbine blade manufacturers are obliged to perform standard ultimate and fatigue tests on their products. In this research a cost effective Blade Testing Machine (BTM) is proposed which is capable of conducting ultimate static and fatigue tests according to wind turbine blade standards. A new control unit is designed and implemented to track fatigue block loading in the frequency range of 1 to 3Hz. The main focus is on designing a controller to perform desired block loading fatigue tests with proper performance. PI and robust feedback controllers are designed and analyzed. Due to the poor robust performance, an adaptive feed forward controller is proposed based on the gain scheduling algorithm. The proposed robust controller compensates un-modeled high frequency dynamics and rejects measurement noises while the adaptive controller compensates low frequency uncertainty and improves reference tracking. Extensive experimentations in the desired frequency range confirm proper performance of the developed controller.

Attitude control of spacecraft is one of the most important issues in aerospace. Different control method for this purpose were proposed that each of these controllers have different behavior against disturbances. One of these methods is backstepping which is divided to adaptive and nonadaptive techniques. Since the spacecraft equations are nonlinear, linear control methods will not work in this case so the nonlinear control methods should be used. The modular adaptive backstepping method is a nonlinear adaptive control method and has a parameter update law that we can use different estimators to estimate system’s unknown parameters in this method. It is also possible to reduce the differentiation load of virtual control laws by using the command filtering method. In this paper, contrary to other works which mostly use discrete command filtering method, we use continuous command filtering method which the natural frequency and damping coefficient can be determined to bring down the computation of the time derivatives of virtual controls laws to differentiation. In this paper, after deriving spacecraft equations in terms of Modified Rodrigues Parameters, we design two stable attitude controllers for spacecraft using standard and command filtered modular adaptive backstepping methods and prove the stability of system using the Lyapunov theory and then simulation results of these controllers are compared with each other. Simulation results show good attitude tracking accuracy and success of adaptive backstepping method in having robustness against disturbance torque is proved

This paper presents dynamic modeling, classical and nonlinear control of flight of mesicopter. First, nonlinear multiple-input multiple-output model is derivedtaking into consideration the bodyandrotorgyroscopiceffects,thenthreeclassical􀀃control􀀃methodsfo 􀀃fast􀀃responsewithhigh performance are used and compared with respect to control􀀃 effort. Mesicopters are􀀃 always affected􀀃byuncertainties.Classicalapproachisnotabletoproperlycompe sate􀀃theseeffects.To overcomethisproblem,modelreferenceadaptivecontrol is used withthr edifferenttypesbased on single-input single-output linear equations, multiple-input􀀃 multiple-output linear equations and nonlinear multiple-input multiple-output equations. Based on the simulation results, the adaptive control method with estimation mechanism improved performance, attitude stabilization and control of system􀀃 states in different conditions. Stability is guaranteed by Lyapunov stability theory.􀀃 Results demonstrate good performance of adaptive control for parameter􀀃uncertaintycompensation.

Actuator failures can cause control system performance deterioration and even lead to instability and catastrophic accidents and incidents. Therefore, the adaptive control of damaged aircraft in designing flight control systems to enhance safety level has recently become the subject of research. Damage causes structural changes and parametric uncertainties which need a new modeling and control approach. In this paper, firstly, a nominal control design based on linear quadratic regulator design is used and shown that the linear quadratic regulator design is not capable of coping with the unknown actuator failure and cannot achieve satisfactory performance. Then, a feedback adaptive signal is designed based on direct approach to handle uncertain actuator failures in linearized system. The adaptive control scheme is applied to the linearized model of a large transport aircraft in which the longitudinal and lateral motions are coupled as the result of using engine differential thrusts. The type of damage which is considered for actuators in this paper is lock-in-place which means control surfaces are fixed in an uncertain value after damage. Analytical stability analysis and simulation results are presented to demonstrate the effectiveness of the proposed approach.