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

This article aims to control the group flight of unmanned helicopters. After presenting the dynamic equations using the Newton-Euler method, the dynamic inversion control has been applied to control the position and attitude of helicopters. generalized predictive control was also used to control the position and attitude of the helicopter. And the results of the simulation of these two controllers were compared, which showed the better performance of the predictive control. Therefore, in the design of the formation control, the independent control of the helicopters was done using the predictive control method. To control the formation, the method based on the leader-follower model has been used, An integral sliding mode controller is also used to control the dynamics of the formation error. The results of the simulation showed the success of the tracking by increasing the number of helicopters and the linear and spiral paths in the control commands.

Parallel manipulators are of interest in various industries due to their high precision, rigidity, high speed and low inertia. Controlling these types of systems faces challenges due to their complex and non-linear dynamics. Among the many methods of controlling the path of parallel manipulators, computed torque and sliding mode methods are the famous methods that are proposed. In practical applications, when the speed of the robot increases, adjusting the controller parameters is very difficult and depends on the working conditions of the robot, so the robot cannot work properly with fixed and predetermined coefficients under any condition. The type of path, the speed of the robot along the path, the initial conditions of the end effector of the robot in relation to the path, and even the sampling time are factors that affect the accuracy of the controller, and by changing each of them, it may be necessary to redefine the parameters of the control system and change the control coefficients. In this article, a method is presented which is based on the sliding mode method and the coefficients of the control system are adjusted appropriately by changing the sliding surface and sliding speed using the fuzzy method. The performance of this method has been investigated in two ways: modeling in MATLAB software and real time applying it to a planar parallel robot.

In this study, in order to enhance the accuracy of tracking repetitive maneuvers in Unmanned Aerial Vehicles (UAVs), a learning-based control scheme is proposed. At the outset, the controller is designed based on the sliding mode control (SMC) technique. In addition, the offline PD-type memory-based iterative learning control (ILC) is used along with SMC. The purpose of using ILC method is to reduce the effect of system uncertainty on the controller and decrease repetitive errors by adjusting the input control signal to dynamics and thus, to increase the reliability of following the desired path. In the ILC scheme, the error of states is saved during the maneuvers which will be used in the subsequent iteration. Also, in order to increase flexibility of the new control structure, ILC-SMC, a multilayer perceptron (MLP) has been developed. This network is designed to extend the control signal, generated by ILC, to similar maneuvers. The inputs of this neural network are the initial conditions for starting the maneuver and the output of the neural network is a gain that is multiplied by the stored control signal ILC and produces a new control signal. This generated signal will be suitable for similar maneuvers. The Levenberg–Marquardt (LM) algorithm has been used to train the multilayer perceptron artificial neural network. This method was then used in loop maneuvers. In this simulation, the difference between the maneuvers was in the acceleration of the maneuver, the radius of the maneuver, and the initial speed of the maneuver. This reduced the tracking error for similar maneuvers without performing the training process for the ILC control component. The presented control scheme is applied to a quadrotor aerial vehicle for tracking desired trajectories and it is shown that the vehicle is able to follow the desired trajectory better than the conventional SMC in the presence of uncertainties.

In this article, various methods have been introduced regarding the movement of robots and the advantages and disadvantages of these methods. By combining the methods of potential function, virtual structure and leader tracking, an algorithm is obtained that, while having the merits of the mentioned methods, also overcomes the disadvantages and challenges of these methods to a large extent. The resulting algorithm is used to design the desired movement path of the robots, and a sliding mode controller acts as a useful tool to force the robots to follow these desired paths. Finally, to evaluate the performance of the designed system, the movement of a group of six non-holonomic robots that surround a target in a triangular formation has been simulated in MATLAB software. The obtained results is compared with the works done by other researchers. It was found that the introduced algorithm has important advantages over previous works, such as reducing the volume of calculations, removing the local minima of potential functions, reducing the range of input changes, the reduction of the number of weight coefficients to adjust the potential functions. It should be noted that the resulting advantages make this method more suitable for practical applications.

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.

In this paper, a fairly comprehensive comparative study has been done on online identification methods for the dynamic model of an aircraft system. To this aim, first, the existing algorithms in this field are introduced. Then, some of these approaches including the recursive least square, the recursive extended least square, the recursive instrumental variable, the extended matrix, the radial basis function neural network, and the multilayer perceptron neural network are utilized to identify the aircraft model. To carry out the simulations, and train the neural networks, the linearized model and online data of the Boeing 747 aircraft controlled by a sliding mode controller on an arbitrary reference trajectory are employed. Finally, the efficiency of each of the above-mentioned methods is evaluated and compared to the other approaches. According to the obtained results of this research, the radial basis function neural network method has a significantly superior performance over the other algorithms due to dynamic noise estimation, independence from the system model, rejecting the linear model of the system, and higher accuracy while maintaining the appropriate speed.

This paper details a new method for model-based discrete sliding mode control of a spark ignition (S.I.) engine cold start considering nonlinear dynamic effects, modeling uncertainty and multiple switched dynamic configurations. Control algorithm deals with stabilization and tracking problems that correspond to crank-shaft velocity, air-to-fuel ratio (AFR) and catalyst temperature in cold start operating mode. To this end, an individual sliding function is assigned to each tracking problem which is subsequently used in construction of associated Lyapunov function. Crank-shaft velocity is regulated using air mass flow rate into intake manifold considering associated dynamic equations describing air mass flow. To ensure precise AFR control, the sliding control model is constructed considering the previously calculated air mass flow rate which leads to nonlinear expressions that are subsequently employed in calculation of appropriate fuel mass flow rate. Stabilization of catalyst temperature is conducted through definition of a virtual control input corresponding to spark angle. As catalyst temperature is described using logarithmic mathematical expressions, additional steps have to be considered to ensure feasibility of control algorithm in various operating conditions. The designed control was numerically applied to validated mathematical model of Toyota 2AZ-FE engine so as to render efficiency and precision of feedback performance.

In this paper, two control methods are presented to control a class of underactuated systems with two degrees of freedom. The design method of the proposed controllers and how to prove the stability of the closed-loop system using solutions such as backstepping control, sliding mode control, fuzzy logic and their combinations are presented in details. Mathematical proof shows that the closed-loop system under the proposed scheme has a global asymptotic stability in the presence of structural and un-structural uncertainties. Then, the advantages and disadvantages of the proposed controls are examined and then some criteria such as simplicity in practical implementation, the control input calculations volume, the adjustment of the control input coefficients, and the amplitude of the control input are used to make comparisons between the suggested controllers. Finally, to evaluate the performance of the proposed controllers, simulations are implemented on the cart-position system with a single-link inverted pendulum. The simulation results confirm the performance of the proposed solutions.

In this paper, mathematical and 3D modeling of a three-legged robotic arm capable of moving objects in rough terrain is first presented. Then, considering the noise and environment disturbances, a suitable control method is proposed. Controlling this robot because of its nonlinear dynamics and the presence of disturbances and environmental effects is a very important and complex issue. Therefore, the controller should be able to set the robot in the right position as quickly as possible and eliminate the effect of environmental disturbances and noise on the system response. Accordingly, in this paper, a Double Hyperbolic Sliding Mode Control based on Unscented Kalman Filter is developed for a three-legged mobile manipulator and system stability is proved by Lyapunov theory. In the proposed controller design, while considering the disturbance term in the dynamic model of the system, an Unscented Kalman Filter is used to reduce the noise effect, which improves the robustness of the system under severe conditions. Finally, the performance of the proposed controller is compared with the inverse dynamic controller and the integral sliding mode control on the robotic system. The results show faster operation speed and accuracy in the system response.

In this paper, an efficient scheme is presented based on fractional order sliding mode control (FOSMC) method for tip position control of a single link flexible robot manipulator. The proposed control strategy is robust against the system parameters variations such as payload and viscous friction variations in the presence of the unknown Coulomb friction disturbances. The main objective of the proposed control scheme is to reduce the deflection due to the flexibility of the link and the precise tip positioning control of the single-link flexible manipulator. To achieve this aim, sliding mode control method is performed in two stages. In the first step, the difference between the motor angle and the tip angle of the flexible link is reduced by applying the proposed fractional order sliding mode controller. Then, in the second step, another sliding mode controller is added to obtain precise control of tip-link position. Numerical simulation results show the feasibility and effectiveness of the proposed control method.

Vibrations due to backlash and other nonlinear effects is a common problem in industries with power transmission systems with gear. Various dynamic models show chaotic behavior in power transmission systems that use spur gears. The aim of this study is to control the chaotic behavior in spur gear transmission system by transferring the system onto an existing unstable periodic orbit and tracking the trajectory using sliding mode control. The proposed model in this study considers a pair of spur gears with time dependent stiffness, backlash and static translation error. Firstly, the dynamic equations are extracted and the effect of model parameters on system response are indicated by simulation results. Then using Poincare’ map and an efficient algorithm, the unstable periodic orbit is detected. Finally, the sliding mode controller is designed to track the desired trajectory obtained from the unstable periodic orbit. The simulation results show the performance of the proposed controller.

Piezoelectric actuators are the most common choice for position control with ultra-high precision. Despite the significant advantages, the linear and nonlinear dynamics of these actuators, such as hysteresis, could decrease the precision of the control system. In this research, a controller based on the sliding mode method is proposed for position control of piezoelectric actuator. Sliding mode control is a model-based and useful method in nanopositioning systems. In this research, Bouc-Wen model is used for description of the actuator’s behavior. In this model, the linear dynamic is modeled with mass, stiffness and damping terms, and the hysteresis is modeled by its nonlinear dynamics. Usually, there are mismatch and uncertainty between the physical system and mathematical model. For stability analysis of the prevalent sliding mode control, the upper bound of uncertainty must be known. But, in practical systems, this is not possible, simply. On the other hand, selecting the large values for this bound, increases the controller gain and distances it from the optimum value. The proposed adaptive robust control eliminates the dependency to the upper bound of uncertainty. This is done by introducing an online adaptive law for estimating this bound. Proposing this law, asymptotic stability of the closed-loop control system is proven. Implementing the presented method on the laboratory setup and simulator software, its effectiveness is shown by simulation and experimental results.

Differential wheeled mobile robot is constructed from two independent active wheels and a spherical passive wheel. This robot as a result of pure rolling and nonslip conditions of wheels is a nonlinear system subjected to nonholonomic constraints. In addition, this system is classified as an underactuated system. Trajectory tracking we have concentrated on is one of the most complicated problems in control of wheeled mobile robots. In the first step a kinematic model in which linear and angular velocity are supposed as system inputs has been presented. Then using a feasible reference trajectory for the first time a novel full state backstepping controller has been designed and unlike previous approaches the stability has been provided fully stated and globally. Next, a sliding mode controller which is based on input-output control theory has been suggested. The proof of stability of this controller has been presented as well. Then a feedback linearization controller as an efficient approach has been proposed with the aim of comparing the performance of the controllers. Finally, integrity and robustness of designed controllers against disturbances have been approved using MATLAB simulation and the obtained results are discussed.

Modeling and control of Unmanned Aerial Vehicle is undoubtedly one of the most active areas in the field of control engineering. The characteristics of aerial vehicles such as nonlinear dynamics, time variability and the structural and parametric uncertainties make flight control issue relatively a complex and important subject. One of the widely used methods in this area is sliding mode control technique. This paper proposes the design, the simulation, and the analysis of two controllers namely PID and sliding mode in order to optimally control the pitch angle of an unmanned aircraft. Initially, in order to model the dynamic system, an appropriate mathematical model is presented to describe the longitudinal motion of aircraft. Subsequently, a robust sliding mode controller is designed using particle swarm optimization (PSO) algorithm to control the pitch angle of an aircraft against the uncertainties and the external disturbances. The optimal parameters are determined by minimizing both the control signal and tracking error. Then, the performance quality of the proposed method was compared with the results of the optimal PID controller in terms of transient response characteristics. Finally, simulation results indicated that the proposed sliding mode controller can reduce the overshoot of system response and yield more robust performance than PID for the control of pitch angle.

A proportional-derivative sliding-mode control (PD-SMC) scheme is addressed for tracking problem of a two-degree of freedom robot manipulator. The sliding-mode control (SMC) may be a robust method in presence of parameters change and system uncertainties. In a typical control problem, the proportional-derivative (PD) control law provides a fast response while the stability of the closed loop system is increased. Hence a two degree of freedom robot manuplator is considered. Then the asymptotic stability of closed loop system with the PD-SMC policy would be shown by using of the well-known Lyapunov stability theory. As a result of this paper, the asymptotic stability criteria would be checked in term of some simple matrix inequalities. Having satisfaction of such matrix inequalities in the tracking problem of the robot manipulator, the tracking error and its derivative would be converged to zero. In order to compare the results with the other control approaches, the controller parameters are firstly tuned in an optimization way via the genetic algorithm (GA) method. Then some numerical examples are provided to show the effectiveness and robustness of the PD-SMC in comparing with the existing methods.

In this paper, a trajectory tracking control of a nonholonomic wheeled mobile robot is proposed based on terminal sliding mode control, and the proposed method has been implemented on a wheeled mobile robot. A wheeled mobile robot is a nonlinear nonholonomic system, and it has three extended coordinates and a nonholonomic constraint. First, the equation of wheeled mobile robot for the extended chained form is derived by transformation of the nonholonomic system equation to the extended chained form. Then a finite time terminal sliding mode approach for trajectory tracking control of the wheeled mobile robot is presented. Afterward, with a graphical simulation environment which is applicable in the Matlab software, graphical simulations of wheeled mobile robot’s movement are done. The result of the graphical simulation in comparing with sliding mode control show the performance of the proposed method. Finally, the practical results of implementation of the controller for trajectory tracking of the wheeled mobile robot is shown, and the results show good tracking performance of the proposed method.

The main purpose of this paper is to the distributed formation tracking for fractional order multi agent systems with the leader-follower approach. First, it discusses the Lyapunov candidate function used to check the stability of the controlled system. The introduced candidate function is based on the properties of the matrix representing the desired system graph of the system. In this phase, the Lyapunov direct method is used to determine the stability of fractional order systems. Then, using sliding mode control, a decentralized controller design for tracking in fractional multi agent systems is presented in which it introduces and verifies the introduced control inputs. In the model, the input system is also considered as a disturbance type, and the control efficiency designed in turbulence mode is shown. In this section, it is shown that the controller introduced in the previous section has a desirable efficiency due to the sliding mode control. In the second section, the stability of the system, such as the first section, is investigated. at the end of this paper, several simulation examples are developed for controlling the performance of the controller.

In this paper, an optimal robust hybrid active force controller based on Harmony Search Algorithm is designed for a lower limb exoskeleton robot. Dynamic equations are derived using Lagrange method by considering three actuators on the hip, knee and ankle joints to track a specific trajectory. One of the major problems of exoskeleton robots is non-synchronization of movements and transfer of power between the robot and human body which affects the robot in form of disturbance. In order to mitigate the effect of disturbances and increase precision, combination of active force control (Corrective loop of control input) with position control is used as an effective and robust method. In the active force control, to elicit robust input control against disturbances, the moment of inertia of the links is estimated at each instant by minimizing the Criteria of ITAE and the control input rate, using the Harmony Search algorithm and the control input is modified. Also, two controllers are designed for the position control loop using sliding mode and feedback linearization methods. In order to validate the performance of the designed controllers, the robot is modeled in ADAMS and control inputs are applied to the Adams model. For appropriate comparison, all control parameters are optimized using the harmony search algorithm and then performance of position controllers are compared in hybrid and conventional (without the force control loop). Results indicate the outperforming of the hybrid sliding mode controller rather than to the other designed controllers.

In this paper, a Sliding Mode Controller (SMC) based on Linear Quadratic Regulator (LQR) method is designed for aircraft landing control system in presence of aerodynamic disturbances. In order to obtain the control law, despite the inversion of input matrix should be calculated, in many practical systems the matrix is a non-square matrix which its inversion is not defined. To solve this problem, some approaches are developed which use pseudo inverse instead of the inversion of input matrix. A special type of transform matrix is employed for designing the proposed controller. The LQR procedure is used for calculating the transform matrix improves the performance of the control system. But in this method the external disturbances and uncertainties are not considered. Hence, the “matrix transform method" is extended for the systems with uncertainties and external disturbances. The propose controller is applied to control autonomous landing of Boeing 747. The simulation results are illustrated to show the performance of the proposed strategy.

In this paper, a quantum intelligent robust controller via a combination of sliding mode control with boundary layer and quantum neural networks, for uncertain nonlinear systems in presence of external disturbances, is presented. Based on the adjustable time variant rejection regulator and rejection parameter, a time variant sliding surface as an adaptive chain of the first ordered low pass filters is defined. A three layers quantum neural network is designed to identify the uncertain nonlinear functions in system dynamics. In this method, the control gain and the break-frequency bandwidth are tuned adaptively. Also, the effects of uncertainties and the un-modeled frequencies are eliminated and chattering phenomenon doesn’t occur. Also, for facilitating analytical theory of the presented method and derivation of the adaptive laws a theorem is proved. Finally, the simulated examples show that the proposed method presents an intelligent adaptive robust tracking control such that the control amplitudes and the integral absolute error index of the tracking trajectory are much less than the other methods. Therefore, effective identification, eliminating the effects of system uncertainties, adjustable control gain and break-frequency bandwidth and more accurate tracking are some of the advantages of this method.