Top PDF Cartesian Parallel Manipulator Modeling, Control and Simulation

Cartesian Parallel Manipulator Modeling, Control and Simulation

Cartesian Parallel Manipulator Modeling, Control and Simulation

Several spatial parallel manipulators with a rotational moving platform, called rotational parallel manipulators (RPMs), were proposed (Di Gregorio, 2001), (Karouia & Herve, 2000) and (Vischer & Clavel, 2000). (Clavel, 1988) at the Swiss Federal Institute of Technology designed a 3-DOF parallel manipulator that does not suffer from the first two of the listed disadvantages of the Stewart manipulator. Closed-form solutions for both the inverse and forward kinematics were developed for the DELTA robot (Gosselin & Angeles, 1989). The DELTA robot has only translational degrees of freedom. Additionally, the position and orientation of the moving platform are uncoupled in the DELTA design. However, the DELTA robot construction does employ spherical joints. (Tsai, 1996) presented the design of a spatial 3-UPU (Universal Prismatic Universal) manipulator and pointed out the conditions that lead to pure translational motion and its kinematics was studied further by (Di- Gregorio & Parenti-Castelli, 1998). (Tsai, 1996) and (Tsai et al., 1996) designed a 3-DOF TPM (Translational Parallel Manipulator) that employs only revolute joints and planar parallelograms. (Tsai & Joshi, 2002) analyzed the kinematics of four TPMs for use in hybrid kinematic machines. (Carricato & Parenti-Castelli, 2001) developed a family of 3-DOF TPMs. (Fang & Tsai, 2002) presented a systematic methodology for structure synthesis 3-DOF TPMs using the theory of reciprocal screws (Kim & Tsai, 2002).
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Modeling and simulation of X quadcopter control

Modeling and simulation of X quadcopter control

The modelling and control of X-quadcopter using a PID Controller has been presented in this paper. The Simulation is performed in Matlab Simulink and the model takes into account the assumptions that the quadcopter body and the propellers are rigid and the structure is supposedly symmetrical. Based on the attitude control commands in the form of desired roll, pitch and yaw angles, the quadcopter control is brought about by PID Controller. The Simulation results illustrate the velocity and position of the quadcopter along three different axes. This paper provides modelling of the UAV and also the projection of its performance based on the designed model. Earlier work on the same topic provided the modelling parameters alone and this paper takes the reference of it and extend it in measuring projections of its dynamic behavior.
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Aircraft Flight Control Simulation Using Parallel Cascade Control

Aircraft Flight Control Simulation Using Parallel Cascade Control

Abstract Aircraft flight simulation is a billion dollar industry worldwide that requires vast engineering resources. A method for modeling flight control systems using parallel cascade system identification is proposed as an addition to the flight simulator engineer’s toolbox. This method is highly efficient in terms of the data collection required for the modeling process since it is a black box method. This means that only the input and the output to the flight control system are required and details of the inner workings of the system can be largely ignored resulting in significantly fewer real data signals that need to be recorded. The paper views on two objectives. One the specific parallel cascade models can be identified that reproduce the behavior of a particular part of an aircraft flight control system. i.e. the pilot input control meet the objective test requirements of a commercial aircraft flight simulator. The second is to produce such a model which also meets the basic requirements for implementation in a working flight simulator.
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Modeling, simulation, and control of cavity flow oscillations

Modeling, simulation, and control of cavity flow oscillations

The foundations of the modern linear stability theory were laid by Rayleigh [1880], who used his new framework to prove remarkable results about the stability of jet profiles. Rayleigh’s theory persists today, virtually unchanged, and this theory, with some modern accoutrements, forms the subject of the present chapter. Linear stability theory will be used frequently in subsequent chapters, to de- scribe the behavior of the shear layer spanning a rectangular cavity. The de- velopments here will be from this perspective, considering the appropriate flow assumptions and boundary conditions. Most of the results are well known, but scattered throughout the literature, so here we collect them in one place, along with a few recent results, such as the adjoint equations and biorthogonality rela- tion developed in sections 2.6 and 2.7. We describe a locally parallel theory, for inviscid flows. We develop the compressible Rayleigh equation, along with the corresponding adjoint equations, and discuss a biorthogonality condition which is useful for expanding arbitrary flow disturbances in terms of eigenfunctions of the Rayleigh problem.
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Submersible Pump Control Modeling and Simulation

Submersible Pump Control Modeling and Simulation

When the downhole system occurs, and the pressure difference between the upper and lower part of the choke valve changes, the choke valve operates; when the revolving speed of the pump tends to be smooth and steady, the choke valve will operate in a full open form. Figures 4-7 are variation curves of various pa- rameters of the oil well under double PI control. The choke valve operates at 120s and 250s. We observe that the pressure of the pump suction inlet closely follows with the preset value and becomes more ac- curate. We also observe that the revolving speed of the motor basically reaches a reasonable value. We can see that the double PI control can be more accurate and rapid to make the pressure closely follow with the set point, thus achieving the purpose of accurate pre- diction model in the case of the same condition of the entire oil production system of the submersible pump.
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Mathematical Modelling, Stability Analysis and Control of Flexible Double Link Robotic Manipulator: A Simulation Approach

Mathematical Modelling, Stability Analysis and Control of Flexible Double Link Robotic Manipulator: A Simulation Approach

The open-loop transfer function in equation (32) can be implemented into Matlab by using the m-file code. The transfer function from the Laplace transforms or from the state space representation can be used. This transfer function assumes that both derivative and integral control will be needed along with proportional control. This open-loop transfer function can be modeled in Matlab. The function polyadd is not originally in the Matlab toolbox. It has to be copied to a new m-file to use it. This transfer function is assumed that both derivative and integral control will be needed along with proportional control. The actual control of this system could be stated by subjecting step input and its response which has been shown in figure 6.
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Simulation of a Mobile Manipulator on Webots

Simulation of a Mobile Manipulator on Webots

Óscar F. Avilés S Was born in Bogotá, Colombia, in 1967. He received the Engi- neer degree in Electronics and Specialist of Electronic Instrumentation of Antonio Nariño University – UAN - in 1995 and 2002, respectively. Master in Automatic Production Systems - Technological University of Pereira - 2006 Colombia and PhD in Mechanical Engineering in Campinas State University – UNICAMP – Brazil. Cur- rently is Professor in the Department of Mechatronics Engineering in Militar Nueva Granada University - UMNG. He has experience in the areas of Electronic Engineer- ing, with emphasis on electronic instrumentation and control systems, acting mainly on the following topics: robotics, control and biomechatronics.
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Inverse dynamics and trajectory tracking control of a new six degrees of freedom spatial 3-RPRS parallel manipulator

Inverse dynamics and trajectory tracking control of a new six degrees of freedom spatial 3-RPRS parallel manipulator

the mobile part of the robot is reduced to the three legs and the mobile platform. Consequently, higher velocities and ac- celerations of the mobile platform can be achieved. Another benefit is that the legs are made of only thin rods, thus, reducing the risk of leg interference. Further, the geomet- rical/physical parameters of the manipulator are also opti- mized for a given constant orientation workspace. The in- verse dynamic model is obtained using the Lagrangian dy- namic formulation method (Abdellatif and Heimann, 2009). The proposed robust task-space trajectory tracking controller is based on a centralized proportional-integral-derivative (PID) control along with a nonlinear disturbance observer. The control schemes for parallel manipulator may be prin- cipally separated into two types, joint-space control estab- lished in joint-space coordinates (Davliakos and Papadopou- los, 2008; Honegger et al., 2000; Kim et al., 2000; Nguyen et al., 1992; Yang et al., 2010), and task-space control designed based on the task-space coordinates (Kim et al., 2005; Ting et al., 2004; Wu and Gu, 2005). The joint-space control ap- proach can be readily employed as an assemblage of several independent single-input single-output (SISO) control sys- tems using the data on each actuator feedback only. A classi- cal PID control in joint-space along with gravity compensa- tion has been employed in industry, but it does not always as- sure a great performance for parallel manipulators. However, the proposed robust task-space control approach improves the overall control performance by rejecting the uncertainty and nonlinear effects in motion equations. The rejections of system or model uncertainty, unknown external disturbance and nonlinear effects in the system motions have been com- pleted in the proposed control scheme with the help of an equivalent control law; a feed-forward control scheme and a nonlinear disturbance observer along with the nonlinear PID control scheme. In the proposed task-space control method, the desired motion of the end effector in task-space is used directly as the reference input of the control scheme. That is, the motion of the end effector can be obtained from the sys- tem sensors and compared with the reference input to form a feedback error in task-space. Therefore, an exact kinemat- ics model is not required in the task-space control, and thus this method is sensitive to joint-space errors or end effector pose errors due to joint clearances and other mechanical in- accuracies. The validity of the proposed control scheme is demonstrated with the help of virtual prototype experiments. The performance of the proposed control scheme including closed-loop stability, precision, sensitivity and robustness is analysed in theory and simulation.
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3-RPS Parallel Manipulator Dynamical Modelling and Control Based on SMC and FL Methods

3-RPS Parallel Manipulator Dynamical Modelling and Control Based on SMC and FL Methods

In the current paper, following the inverse and forward kinematical modeling, under the assumption that the leg inertia is negligible, the dynamical model of the 3-RPS manipulator is obtained using Lagrange method. Considering six dependent generalized coordinates in the modeling process, and by applying the principle of virtual work, the distribution matrix of control input vector in the formulation appears as an identity matrix. Therefore, mathematical manipulation and computational burden significantly decrease. The present method can be applied to nonholonomic systems as well. With following linearization, the error dynamics of the 3-RPS through the computed torque method, an SMC law is applied to stabilize the robot around its reference trajectories even in the presence of exogenous disturbances, and uncertainties in the model . Through software simulation, the superiority of the proposed control system is compared with a FL control method. As can be seen, both the SMC and FL control systems yield the convergence of the end-effector to the reference trajectory when there is no disturbance and no parameter uncertainty. Although disturbances do not affect the performance of the FL controller, parameter uncertainties especially uncertain geometrical specifications lead to malfunction of the FL controller. However, as a robust control approach, the proposed SMC system results in satisfactory tracking performance against all the above- mentioned uncertainties and exogenous inputs.
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Simulation design of trajectory planning robot manipulator

Simulation design of trajectory planning robot manipulator

This paper is organized as follows, applied SOM neural network to get the best path from the point that spread randomly on the robot manipulator. This robot manipulator is also given a control using Proportional Integral Derivative (PID) and Fuzzy Proportional Derivative (Fuzzy-PD) [12-16]. The reason to combineboth of SOM neural network and Fuzzy-PD control to simulate robot manipulator in this research because it is still rarely used. The advantage of SOM's neural network for trajectory planning robot arm manipulator is the learning process without guidance, unlike the neural network back propagation that should always be guided to learn trajectory planning [17-21]. This robot manipulator simulation is usingMatlab Robotics Toolbox, where the simulation is not built from beginning [5, 6]. The simulation was made by using C# programming languages and the results are displayed with images in 2 dimensional fields. The purpose of this joint implementation research between SOM neural network and Fuzzy-PDcontrol can be the basic research in the realization process later.
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A Vectorial DEVS Extension for Large Scale System Modeling and Parallel Simulation

A Vectorial DEVS Extension for Large Scale System Modeling and Parallel Simulation

Here we again used the automatic partitioning algorithm to split the model of Fig. 4 into 11 sub- models. The resulting model has 11 Airs blocks with out any connections. We then added manually the Control PI (the 12-th block) and its connection. This is done because the algorithm for automatic partitioning does not take into account blocks like the vector sum. This block is neither pure vectorial, nor does event routing or acts as an interface. The kind of computation it performs (a reduction) needs special treatment in the algorithm that is not yet included.

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Power-port modelling of an in-plane 3 DOF parallel micro-manipulator with feed-forward position control

Power-port modelling of an in-plane 3 DOF parallel micro-manipulator with feed-forward position control

Figure 6.1 shows the measured data points together with linear best-fit lines (using the Matlab function ‘polyfit’), as well as the simulated data for the three platform coordinates. A negative voltage means a voltage on the pull comb-drive and a positive voltage means a voltage on the push comb-drive. In the x and y-direction the simulation and measurements match well. For the ϕ-rotation it matches less well. This is due to the fact that the real thickness of the flexures and comb-drive teeth is not known very accurately, so the real stiffness might be different, as well as the comb-drive strength. Especially because the stiffness depends on the thickness to the third power. Hence, a 5% deviance in thickness already becomes a 16% deviance in stiffness and this will also change the voltage-deflection relation.
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Development of a 6 DOF Parallel Serial Hybrid Manipulator

Development of a 6 DOF Parallel Serial Hybrid Manipulator

The new design is based using a modular approach that have large reachable dextrous workspace along with desired rigidity and positional accuracy for diverse applications. For this purpose, a simple hybrid parallel serial manipulator is proposed after design and feasibility study. In this system, a serial arm is coupled with parallel platform to provide the base motion. The development of the hybrid manipulator system covers mechanical system design, system dynamic modelling and simulation, design optimization, trajectory generation and control system design. The different aspects under hybrid manipulator motion control scheme are shown in figure.5. These aspects of manipulation and control includes
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Dynamic Modeling and Simulation of a Rotating Single Link Flexible Robotic Manipulator Subject to Quick Stops

Dynamic Modeling and Simulation of a Rotating Single Link Flexible Robotic Manipulator Subject to Quick Stops

In this paper the modelling and dynamic response of a constrained single link flexible rotating manipulator subject to quick stops was investigated. One end of the flexible manipulator was constrained to a predefined trajectory for possible trajectory control and obstacle avoidance. The effect of link flexibility, axial shortening and clearance has been considered in the analysis of the rotating flexible manipulator. It was observed that the time evolution of the system was mainly affected by the quick stops and angular velocity. At the time of the quick stop (which represents the main impacts of the system) the flexible link makes successive shocks, which increase the amplitude of vibration. Further experimental tests will be performed in order to validate and generalize the simulations reported in this study.
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Design, Simulation and Mathematical Modeling of a RPR Manipulator for Collecting Waste from Beans

Design, Simulation and Mathematical Modeling of a RPR Manipulator for Collecting Waste from Beans

So, from the equation (II) to (VI) the position with respect to base, rotation matrix, torque, singularity and joint angles can be determined. Following these solutions the trajectory can be planned very easily and such a manipulator will perform our desired activity more smoothly and accurately in comparison with human being. Just following the algorithm in a microcontroller, this robot can perform its job quicker than a man. Yet this research has lots of scopes for working still now. The control system can be designed and many features can be added to the manipulator for more perfect operations. Hence, this research was regarding the mathematical model and performance of the manipulator which the vehicle carries; this paper will help the researchers at this field as well as those who are trying to make a mean of utilizing manipulators in the field of waste management for reducing the possibility of health diseases to human beings and to reduce the anxiety of regular collection of waste in municipal areas.
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Kinematics, Structural Analysis and Control of 3 PPSS Parallel Manipulator

Kinematics, Structural Analysis and Control of 3 PPSS Parallel Manipulator

al. [8] introduced a 3 DoF parallel manipulator for medical applications. The dynamic equations for each leg are written separately and finally coupled together using suitable constraints. Each leg is approximated as a serial manipulator. The constraints are reintroduced into the model by the use of Lagrangian multipliers.Pedrammehr et al.[9] developed a 6 DoF parallel manipulator called Hexarot. Hexarot robot comprises of six arms which is collectively connected to the triangular platform. The mechanism is modelledkinematically in terms of Euler angles. The mechanism is modelled dynamically using the Newton-Euler approach and verified using ADAMS. The author presented a simulation study for defined joint motions and correspondingly compared the results obtained from the dynamic model and ADAMS. Chablatet al. [10] explained the inverse kinematics and dynamics of an orthoglide parallel robot
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Modeling And Simulation Of 3 Degree Of Freedom Of Robot Manipulator

Modeling And Simulation Of 3 Degree Of Freedom Of Robot Manipulator

The 3 degree of freedom robot manipulator in this project is RRR robot arm, which has 3 revolute joints. So basically, the mathematical models are kinematic model, inverse kinematic model of robot manipulator and 7-DOF vehicle ride model. So in PSM 1 the mathematic derivation will be completed until forward kinematic and PSM 2 is inverse kinematic, 7-DOF ride model and pitch rejection control.

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Control Techniques for Robot Manipulator Systems with Modeling Uncertainties

Control Techniques for Robot Manipulator Systems with Modeling Uncertainties

The control objective in many robot manipulator applications is to command the end-effector motion to achieve a desired response. To achieve this objective a mapping is required to relate the joint/link control inputs to the desired Cartesian position and orientation. If there are uncertainties or singularities in the mapping, then degraded performance or unpredictable responses by the manipulator are possible. To address these issues, in this chapter, an adaptive task-space tracking controller is developed for robot manipulators with uncertainty in the kinematic and dynamic models. The controller is developed based on the unit quaternion representation so that singular- ities associated with three parameter representations are avoided. In addition, the developed controller does not require the measurement of the task-space velocity. The stability of the controller is proven through a Lyapunov based stability analysis. Simulation results using a two degree of freedom planar manipulator model are pre- sented to validate the controllers performance, then experimental results for a planar application of the Barrett whole arm manipulator (WAM) are provided to illustrate the performance of the developed controller.
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MODELING, SIMULATION AND DYNAMIC ANALYSIS OF TRICEPT PARALLEL MANIPULATOR

MODELING, SIMULATION AND DYNAMIC ANALYSIS OF TRICEPT PARALLEL MANIPULATOR

In general, it can be accepted that robot manipulators having the end effector connected to the ground via several chains having actuation in parallel will have greater rigidity and superior positioning capability. Thus makes the parallel manipulators attractive for certain applications and the last two decades have witnessed considerable research interest in this direction. Industrial robots play a central role in factory automation. However, there has been little effort as to the application of application of robots in machining work such as grinding, cutting, milling, drilling etc. This kind of work requires robot manipulators to have high stiffness, rigidity and accuracy which cannot be provided by conventional serial robot manipulators. Hence for the application like these it is desirable to have parallel manipulators.
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Design and Implementation of the Remote Control of the Manipulator

Design and Implementation of the Remote Control of the Manipulator

The description of one fi nished work using the remote control system follows as a proof of concept of the whole remote control system. This work is focused on fi nding position, orientation and dimensions of the objects that are placed in the working space of the manipulator. The stereoscopic images from two cameras, described above, connected to the upper parts of the protective cage (see Fig. 1), are used for fi nding these parameters. Moreover, the stereoscopic analysis provides spatial dependencies between objects and also provides required information about the working space, which is useful for planning the motion of the manipulator. This analysis is focused on transformation of the depth map, obtained from the stereoscopic view, to the space of parallel coordinates. There is dualism between the new representation based on parallel coordinates and the Cartesian system, in which the stereoscopic images were taken. The searched lines of the objects are transformed to the points in the parallel coordinates, thanks to the dualism. These points are independent of rotation and can be found easily. The various methods such as thresholding or fi nding the maximum of the cut of parallel point were successfully tested for fi nding these points. See more details in our previous work (Kolomazník, 2013).
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