جستجوی مقالات مرتبط با کلیدواژه « سکوی استوارت » در نشریات گروه « مکانیک »

Endeavor achieving as much as realistic perception of motion in motion cueing design are shifted towards utilizing the general nonlinear models of the motion systems. However, this approach is computationally more demanding. Hence, using efficient computational algorithms are essential to fulfill the requirements of high computing speed and accuracy without any interruption in real-time operations. Takagi - Sugeno fuzzy system as a major sector of soft computing characterized by effectively dealing with nonlinear processes, high computational speed, and easy implementation is used to approximate the nonlinear inverse kinematic of the motion system model by fuzzy interpolation of the set of linear sub models. The augmented linear parameter varying motion cueing model is constructed incorporating the fuzzy approximated inverse kinematics of the motion system along with the human perception of motion. The complete motion cueing model is computed using real-time model predictive control approach considering all physical constraints. The results of simulation show remarkable improvements in terms of less and smooth movements of actuators, hence much efficient use of motion system’s workspace compared to its general nonlinear counterpart, which reveals an effective alternative in real-time applications.

This paper presents a nonlinear predictive approach, for Stewart platform (6 degrees of freedom). The optimal control is computed directly from the minimization of receding horizon cost function with offline optimization. The main purpose of this research is designing the predictive controller for Stewart platform. In this study, the kinematics and dynamics of Stewart robot is introduced, considering the dynamics of actuators. Following the introduction of nonlinear model predictive control will be discussed and according to robot dynamics, controller will be design. In addition, given the various uncertainties, robot dynamic equation could be rewritten. The controller is designed according to these uncertainties and then stability control is confirmed using Lyapunov theory. Due to the limited engine power and the output torque electric drive in practice, the proposed controller manages Stewart platform in such a way that it could track the desired trajectory well. To review the proposed method at the end of the study, Stewart platform is simulated and the control method proposed in this paper was compared with computed torque control (CTC) method, sliding mode control and Proportional-Integrator-Differentiation (PID) controller.

The Stewart platform with six degree of freedom (three translational and three rotational motions) consists of two rigid bodies, lower plate (base) and upper one (mobile). These two bodies are connected together by six extensible legs between three pairs of joints on each of the bodies. This platform can be used to isolate the top plate of the platform and its payload from the applied motions to the base. Since the passive isolation methods are not effective in elimination of the high amplitude (and usually) low frequency motions, this paper practically investigates the possibility of using the 6DOF Stewart platform as an active vibration isolator. In this study, a Stewart platform was designed and constructed based on electric actuators (servo-motors). And then it was practically utilized to isolate its top plate from the applied pitch and roll rotations to the base plate. MEMS sensors including two accelerometers and one rate gyro along with Kalman filter and kinematic relations were utilized for measuring the pitch and roll motions. A PI controller was implemented to keep the top plate at level position using the MEMS sensors installed on the bottom plate. The experimental results indicated that the platform can effectively isolate the pitch and roll motions while the frequency of these motions is in the working speed range of the electric actuators.

Skilled pilot training in aviation industry is of great importance. This in real terms due to high costs and safety considerations، is facing with serious obstacles. Thus providing low cost، efficient and repeatable flight training conditions attracted a broad range of researches. Flight simulators are such devices for training the skilled pilots. These tools aim to provide the same feeling of real flying for pilots، and give the opportunity to pilot to react under terms of the flight conditions. Motion cueing design algorithm is of the salient challenges in the design of these devices. The algorithm receives the linear acceleration and angular velocity of the real flight as the inputs and is due to calculate the appropriate movements of the actuators such that the infinite plane motions to get constricted to finite motions in the limited work space of the flight simulator. This has to be done in a way that the pilot in flight simulator feels as could as the same sense of motion of the pilot in aircraft. The authors aim to develop an optimal motion cueing algorithm for 6 DoF flight simulator with fuzzy compensated system specially focusing on the maximum use of workspace of the simulator to obtain more appropriate sense of motion. Comparing the results of the proposed fuzzy compensated and the conventional optimal motion cueing algorithms، shows an evident improvements in terms of smaller movements of actuators while achieving more appropriate motions of the flight simulator.