SU-E-T-543: The Use of a Proportional-Integral-Derivative Design for Optimized Real-Time Head Motion Correction in Frameless SRS

2011 ◽  
Vol 38 (6Part19) ◽  
pp. 3614-3614
Author(s):  
J Rosenfield ◽  
Z Grelewicz ◽  
H Kang ◽  
R Wiersma
Keyword(s):  
Real Time ◽  
Motion Correction ◽  
Head Motion ◽  
Proportional Integral Derivative ◽  
Proportional Integral

Dynamic modeling, system identification and comparative study of various control strategies for a spatial parallel manipulator

2021 ◽  
pp. 095965182110320
Author(s):  
Mervin Joe Thomas ◽  
Shoby George ◽  
Deepak Sreedharan ◽  
ML Joy ◽  
AP Sudheer
Keyword(s):  
Real Time ◽  
Parallel Manipulator ◽  
Control Strategies ◽  
Proportional Integral Derivative ◽  
Real Time Control ◽  
Model Predictive Controller ◽  
End Effector ◽  
Proportional Integral ◽  
Time Control ◽  
Predictive Controller

The significant challenges seen with the mathematical modeling and control of spatial parallel manipulators are its difficulty in the kinematic formulation and the inability to real-time control. The analytical approaches for the determination of the kinematic solutions are computationally expensive. This is due to the passive joints, solvability issues with non-linear equations, and inherent kinematic constraints within the manipulator architecture. Therefore, this article concentrates on an artificial neural network–based system identification approach to resolve the complexities of mathematical formulations. Moreover, the low computation time with neural networks adds up to its advantage of real-time control. Besides, this article compares the performance of a constant gain proportional–integral–derivative (PID), variable gain proportional–integral–derivative, model predictive controller, and a cascade controller with combined variable proportional–integral–derivative and model predictive controller for real-time tracking of the end-effector. The control strategies are simulated on the Simulink model of a 6-degree-of-freedom 3-PPSS (P—prismatic; S—spherical) parallel manipulator. The simulation and real-time experiments performed on the fabricated manipulator prototype indicate that the proposed cascade controller with position and velocity compensation is an appropriate method for accurate tracking along the desired path. Also, training the network using the experimentally generated data set incorporates the mechanical joint approximations and link deformities present in the fabricated model into the predicted results. In addition, this article showcases the application of Euler–Lagrangian formalism on the 3-PPSS parallel manipulator for its dynamic model incorporating the system constraints. The Lagrangian multipliers include the influence of the constraint forces acting on the manipulator platform. For completeness, the analytical model results have been verified using ADAMS for a pre-defined end-effector trajectory.

Enhanced variable universe fuzzy proportional–integral–derivative control of structural vibration with real-time adaptive contracting–expanding factors

2021 ◽  
pp. 107754632110026
Author(s):  
Gang Liu ◽  
Wei Jiang ◽  
Qi Wang ◽  
Tao Wang
Keyword(s):  
Real Time ◽  
Control Method ◽  
Magnetorheological Damper ◽  
Frame Structure ◽  
Structural Vibration ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Variable Universe ◽  
Proportional Integral Derivative Control ◽  
Derivative Control

A conventional variable universe fuzzy proportional–integral–derivative control approach is widely used for semi-active control in mechanical engineering. The performance of the controller is dependent on an optimal selection of parameters of the contracting–expanding factors. An improved variable universe fuzzy proportional–integral–derivative control algorithm is developed in this study where these parameters are automatically determined in real-time according to the error in the controlled responses and its change rate based on fuzzy logic control. The proposed method is numerically and experimentally illustrated with a three-story frame structure with a magnetorheological damper. The amplitude of displacement, velocity, and acceleration at all floor levels under the proposed control method are smaller than those obtained from existing proportional–integral–derivative, fuzzy, and conventional variable universe fuzzy methods.

scholarly journals Prospective real-time head motion correction using inductively coupled wireless NMR probes

2013 ◽  
Vol 72 (4) ◽  
pp. 971-985 ◽  
Author(s):  
Saikat Sengupta ◽  
Sasidhar Tadanki ◽  
John C. Gore ◽  
E. Brian Welch
Keyword(s):  
Real Time ◽  
Motion Correction ◽  
Head Motion ◽  
Inductively Coupled

scholarly journals Flight Motion Controller Design using Genetic Algorithm for a Quadcopter

2018 ◽  
Vol 51 (3-4) ◽  
pp. 59-64 ◽  
Author(s):  
Huu Khoa Tran ◽  
Thanh Nam Nguyen
Keyword(s):  
Genetic Algorithm ◽  
Real Time ◽  
Controller Design ◽  
Fitness Function ◽  
Absolute Error ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Time Operation ◽  
Real Time Operation ◽  
Effective Stability

In this study, the Genetic Algorithm operability is assigned to optimize the proportional–integral–derivative controller parameters for both simulation and real-time operation of quadcopter flight motion. The optimized proportional–integral–derivative gains, using Genetic Algorithm to minimum the fitness function via the integral of time multiplied by absolute error criterion, are then integrated to control the quadcopter flight motion. In addition, the proposed controller design is successfully implemented to the experimental real-time flight motion. The performance results are proven that the highly effective stability operation and the reliable of waypoint tracking.

scholarly journals Robotic real-time translational and rotational head motion correction during frameless stereotactic radiosurgery

2015 ◽  
Vol 42 (6Part1) ◽  
pp. 2757-2763 ◽  
Author(s):  
Xinmin Liu ◽  
Andrew H. Belcher ◽  
Zachary Grelewicz ◽  
Rodney D. Wiersma
Keyword(s):  
Stereotactic Radiosurgery ◽  
Real Time ◽  
Motion Correction ◽  
Head Motion

Real-time application of IMC-PID-FO multi-loop controllers on the coupled tanks process

2021 ◽  
pp. 095965182098306
Author(s):  
Tassadit Chekari ◽  
Rachid Mansouri ◽  
Maamar Bettayeb
Keyword(s):  
Real Time ◽  
Fractional Order ◽  
Internal Model ◽  
Time Windows ◽  
Nonlinear Behavior ◽  
Internal Model Control ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Model Control ◽  
Reduction Effect

The coupled tanks process is a two input-two output system. It presents a nonlinear behavior and interactions characteristic. After the nonlinear model is obtained, it is linearized around an operating point. A fractional-order proportional–integral–derivative based on the internal model control paradigm (1DOF-IMC-PID-FO) multi-loop controller is determined without considering the interactions, and a fractional-order proportional–integral–derivative based on the 2-degree-of-freedom internal model control structure (2DOF-IMC-PID-FO) multi-loop controller is determined by considering the interactions. Thus, an interactions reduction effect controller is calculated. Both controllers are implemented on a real-time process using the Real Time Windows Target of MATLAB. The objective of the control is to maintain the water level in the lower tanks at desired values. In the experiment, setpoint tracking and disturbance rejection tests are carried out to assess the performance of both 1DOF and 2DOF-IMC-PID-FO multi-loop controllers.

scholarly journals Design, implementation, control and optimization of single stage pilot scale reverse osmosis process

2021 ◽  
Author(s):  
G. Guna ◽  
D. Prabhakaran ◽  
M. Thirumarimurugan
Keyword(s):  
Objective Function ◽  
Real Time ◽  
Reverse Osmosis ◽  
Absolute Error ◽  
Pilot Scale ◽  
Single Stage ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Squared Error ◽  
Integral Time

Abstract In this paper, a single-stage pilot-scale RO (Reverse Osmosis) process is considered. The process is mainly used in various chemical industries such as dye, pharmaceutical, Beverage, and so on. Initially, mathematical modeling of the process is to be done followed by linearization of the system. Here a dual loop construction with a master and a slave is used. The slave uses the conventional PID (Proportional Integral Derivative) with a reference model of the RO process and the master uses the FOPID (Fractional Order Proportional Integral Derivative) with a real time RO process. The slave's output is compared with output of the real time RO process to obtain the error which is in turn used to tune the master. The slave controller is tuned using Ziegler Nicholas method and the error criterion such as IAE (Integral Absolute Error), ISE (Integral Squared Error), ITSE (Integral Time Squared Error), ITAE (Integral Time Absolute Error) are calculated and the minimum among them was chosen as the objective function for the master loop tuning. Hence the tuning of the controller becomes a whole. Therefore two optimization techniques such as PSO (Particle Swarm Optimization) and Bacterial Foraging Optimization Algorithm (BFO) are used for the tuning of the master loop. From the calculations the ITSE was having the minimum value among the performance indices hence it was used as the objective function for the BFO and PSO. The best-tuned values will be obtained with the use of these techniques and the best among all can be considered for various industrial applications. Finally, the performance of the process is compared with both techniques and BFO outperforms the PSO from the simulations.

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