Nonlinear Model Predictive Controller for the Real-Time control of Fast Dynamic System

2019 ◽  
Author(s):  
Supriya P. Diwan ◽  
Shraddha S. Deshpande
Keyword(s):  
Dynamic System ◽  
Real Time ◽  
Nonlinear Model ◽  
Real Time Control ◽  
Model Predictive Controller ◽  
The Real ◽  
Time Control ◽  
Predictive Controller ◽  
Fast Dynamic

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.

Using graphs to construct a math model of a microcontroller-based system for preset rate control of a flywheel motor to be used in high-dynamics spacecraft

2020 ◽  
pp. 126-134
Author(s):  
Vladimir V. NEKRASOV
Keyword(s):  
Real Time ◽  
Rotation Rate ◽  
Control Function ◽  
Real Time Control ◽  
Math Model ◽  
The Real ◽  
Time Control ◽  
Power Matrix ◽  
High Dynamics ◽  
Stated Problem

Developing a microcontroller-based system for controlling the flywheel motor of high-dynamics spacecraft using Russian-made parts and components made it possible to make statement of the problem of searching control function for a preset rotation rate of the flywheel rotor. This paper discusses one of the possible options for mathematical study of the stated problem, namely, application of structural analysis based on graph theory. Within the framework of the stated problem a graph was constructed for generating the new required rate, while in order to consider the stochastic case option the incidence and adjacency matrices were constructed. The stated problem was solved using a power matrix which transforms a set of contiguous matrices of the graph of admissible solution edge sequences, the real-time control function was found. Based on the results of this work, operational trials were run for the developed control function of the flywheel motor rotor rotation rate, a math model was constructed for the real-time control function, and conclusions were drawn about the feasibility of implementing the results of this study. Key words: Control function, graph, incidence matrix, adjacency matrix, power matrix, microcontroller control of the flywheel motor, highly dynamic spacecraft.

Optimization of the real-time control strategy in petroleum-refining catalyst production wastewater treatment with shortcut nitrification

RSC Advances ◽  
2015 ◽  
Vol 5 (105) ◽  
pp. 86490-86496 ◽  
Author(s):  
Tianqi Ma ◽  
Shaohui Guo ◽  
Zhihui Guo ◽  
Qiushi Zhu ◽  
Jinfu Chen
Keyword(s):  
Wastewater Treatment ◽  
Real Time ◽  
Control Strategy ◽  
Control Parameter ◽  
Petroleum Refining ◽  
Real Time Control ◽  
High Ph ◽  
The Real ◽  
Time Control ◽  
Catalyst Production

Indicated high pH benefits the accuracy of real-time control strategy, explained why DO as a control parameter is unreliable.

Real-Time Pseudodielectric Function of Low-Temperature-Grown GaAs

2000 ◽  
Vol 618 ◽  
Author(s):  
D.A. Gajewski ◽  
J.E. Guyer ◽  
J.J. Kopanski ◽  
J.G. Pellegrino
Keyword(s):  
Low Temperature ◽  
Real Time ◽  
Diffuse Reflectance Spectroscopy ◽  
High Energy ◽  
Real Time Control ◽  
The Real ◽  
Time Control ◽  
Active Feedback ◽  
Low Temperature Grown Gaas ◽  
Lt Gaas

ABSTRACTWe present the real-time pseudodielectric function <ε(E)> of low-temperature-grown GaAs (LT-GaAs) thin films during the growth as a function of growth temperature Tg and thickness. We obtained accurate measurements of the real-time <εc(E)> by using in situspectroscopic ellipsometry (SE) in conjunction with active feedback control of the substrate temperature using diffuse reflectance spectroscopy. We show that for epitaxial LT-GaAs layers, the peak in the imaginary pseudodielectric function <ε2(E)> decreases in amplitude and sharpness systematically with decreasing Tg. We also revealed an abrupt change in <εc(E)> near the critical epitaxial thickness hepi, the value of which decreases with decreasing Tg. Above hepi, the LT-GaAs grows polycrystalline (amorphous) above (below) Tg ∼ 190°C. We also simultaneously monitored the surface roughness and crystallinity by using real-time reflection high-energy electron diffraction (RHEED). These results represent progress in obtaining real-time control over the composition and morphology of LT-GaAs

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