scholarly journals Modeling, Simulation, and Vision-/MPC-Based Control of a PowerCube Serial Robot

2020 ◽  
Vol 10 (20) ◽  
pp. 7270
Author(s):  
Jörg Fehr ◽  
Patrick Schmid ◽  
Georg Schneider ◽  
Peter Eberhard
Keyword(s):  
Nonlinear Model ◽  
Linear Time ◽  
Low Cost ◽  
A Priori ◽  
Experimental Studies ◽  
Time Varying ◽  
Serial Robot ◽  
The One ◽  
Feed Forward Controller ◽  
Control Feedback

A model predictive control (MPC) scheme for a Schunk PowerCube robot is derived in a structured step-by-step procedure. Neweul-M2 provides the necessary nonlinear model in symbolical and numerical form. To handle the heavy online computational burden concerning the derived nonlinear model, a linear time-varying MPC scheme is developed based on linearizing the nonlinear system concerning the desired trajectory and the a priori known corresponding feed-forward controller. Camera-based systems allow sensing of the robot on the one hand and monitoring the environments on the other hand. Therefore, a vision-based MPC is realized to show the effects of vision-based control feedback on control performance. A semi-automatic trajectory planning is used to perform two meaningful experimental studies in which the advantages and restrictions of the proposed (vision-based) linear time-varying MPC scheme are pointed out. Everything is implemented on a slim, low-cost control system with a standard laptop PC.

Biorthogonal Wavelet Based Identification of Fast Linear Time-Varying Systems—Part II: Algorithms and Performance Analysis12

2000 ◽  
Vol 123 (4) ◽  
pp. 593-600 ◽  
Author(s):  
Haipeng Zhao ◽  
Joseph Bentsman
Keyword(s):  
System Dynamics ◽  
High Speed ◽  
Linear Time ◽  
A Priori ◽  
Time Varying ◽  
Function Decomposition ◽  
Time Varying Systems ◽  
Random Disturbances ◽  
And Performance ◽  
Short Time

The present work proposes a new class of algorithms for identification of fast linear time-varying systems on short time intervals, based on the biorthogonal function decomposition. When certain features of the system dynamics are known a priori, the algorithms admit their embedding into the identification procedure through the choice of the matching bases, yielding the rapidly convergent identification laws. The speed-up is attained via utilizing both time and frequency localized bases, permitting identification of fewer coefficients without noticeable loss of accuracy. Simulation shows that the resulting high speed identification algorithms can reject small persistent random disturbances as well as capture the fast changes in system dynamics. The algorithm development is based on the results of Part I where it is shown that the sets of all bounded-input-bounded-output (BIBO) stable or l2-stable linear discrete-time-varying (LTV) systems are Banach spaces, and modeling and identification of these systems are reducible to linear approximation problems in a Banach space setting.

Control of a Linear Time-Varying System With a Forward Riccati Formulation in Wavelet Domain

2016 ◽  
Vol 138 (10) ◽  
Author(s):  
Biswajit Basu ◽  
Andrea Staino
Keyword(s):  
Linear Time ◽  
Control Strategies ◽  
Linear Quadratic Regulator ◽  
Time Varying ◽  
Wavelet Domain ◽  
Nonlinear Controller ◽  
Linear Quadratic ◽  
Time Frequency ◽  
Future System ◽  
Control Feedback

A wavelet domain forward differential Ricatti formulation is proposed in this paper for control of linear time-varying (LTV) systems. The control feedback gains derived are time-frequency dependent, and they can be appropriately tuned for each wavelet scale or frequency band. The gains in the proposed forward formulation are functions of the present and past states and hence lead to a nonlinear controller. This nonlinear controller does not require information or approximation about future system matrices. The proposed controller is suitable for systems with time-varying (TV) system matrices and also for controlling transient dynamics. The performance of the proposed controller is compared with two other control strategies, namely, a TV linear quadratic regulator (LQR) based on a backward formulation of the differential Ricatti equation (DRE) and a multiscale wavelet-LQR controller based on asymptotic assumptions. Two numerical examples demonstrate promising results on the performance of the controller.

A Relativistic Newtonian Mechanics Predicts with Precision the Results of Recent Neutrino-Velocity Experiments

2014 ◽  
Vol 6 (1) ◽  
pp. 1032-1035 ◽  
Author(s):  
Ramzi Suleiman
Keyword(s):  
Null Hypothesis ◽  
Experimental Studies ◽  
Theoretical Models ◽  
Newtonian Mechanics ◽  
Speed Of Light ◽  
Symmetry Principle ◽  
Proposed Model ◽  
Significant Difference ◽  
The One ◽  
Complete Collapse

The research on quasi-luminal neutrinos has sparked several experimental studies for testing the "speed of light limit" hypothesis. Until today, the overall evidence favors the "null" hypothesis, stating that there is no significant difference between the observed velocities of light and neutrinos. Despite numerous theoretical models proposed to explain the neutrinos behavior, no attempt has been undertaken to predict the experimentally produced results. This paper presents a simple novel extension of Newton's mechanics to the domain of relativistic velocities. For a typical neutrino-velocity experiment, the proposed model is utilized to derive a general expression for . Comparison of the model's prediction with results of six neutrino-velocity experiments, conducted by five collaborations, reveals that the model predicts all the reported results with striking accuracy. Because in the proposed model, the direction of the neutrino flight matters, the model's impressive success in accounting for all the tested data, indicates a complete collapse of the Lorentz symmetry principle in situation involving quasi-luminal particles, moving in two opposite directions. This conclusion is support by previous findings, showing that an identical Sagnac effect to the one documented for radial motion, occurs also in linear motion.

COMPUTATIONAL AND EXPERIMENTAL STUDIES OF A LOW-EMISSION BURNER FOR A PERSPECTIVE TURBOJET ENGINE WITH THE COMPRESSION RATIO EXCEEDING 40

2020 ◽  
Author(s):  
M. A. Danilov ◽  
◽  
M. V. Drobysh ◽  
A. N. Dubovitsky ◽  
F. G. Markov ◽  
...  
Keyword(s):  
Compression Ratio ◽  
Experimental Studies ◽  
The Other ◽  
Aircraft Engines ◽  
Engine Efficiency ◽  
Other Hand ◽  
Turbojet Engine ◽  
Low Emission ◽  
Civil Aircraft ◽  
The One

Restrictions of emissions for civil aircraft engines, on the one hand, and the need in increasing the engine efficiency, on the other hand, cause difficulties during development of low-emission combustors for such engines.

The system of indicators of the quality of the carbon-carbon composite materials and technologies of their production

2018 ◽  
pp. 127-132
Author(s):  
T. N. Antipova ◽  
D. S. Shiroyan
Keyword(s):  
Composite Material ◽  
Low Cost ◽  
Experimental Studies ◽  
Carbon Matrix ◽  
Carbon Composite ◽  
Optimal Number ◽  
Laboratory Equipment ◽  
Carbon Composite Material ◽  
Carbon Composite Materials

The system of indicators of quality of carbon-carbon composite material and technological operations of its production is proved in the work. As a result of the experimental studies, with respect to the existing laboratory equipment, the optimal number of cycles of saturation of the reinforcing frame with a carbon matrix is determined. It was found that to obtain a carbon-carbon composite material with a low cost and the required quality indicators, it is necessary to introduce additional parameters of the pitch melt at the impregnation stage.

Drug Target Group Prediction with Multiple Drug Networks

2020 ◽  
Vol 23 (4) ◽  
pp. 274-284 ◽  
Author(s):  
Jingang Che ◽  
Lei Chen ◽  
Zi-Han Guo ◽  
Shuaiqun Wang ◽  
Aorigele
Keyword(s):  
Drug Target ◽  
Low Cost ◽  
Machine Learning Algorithms ◽  
Classification Model ◽  
Support Vector ◽  
Multiple Drug ◽  
Property A ◽  
Multiple Networks ◽  
Proposed Model ◽  
The One

Background: Identification of drug-target interaction is essential in drug discovery. It is beneficial to predict unexpected therapeutic or adverse side effects of drugs. To date, several computational methods have been proposed to predict drug-target interactions because they are prompt and low-cost compared with traditional wet experiments. Methods: In this study, we investigated this problem in a different way. According to KEGG, drugs were classified into several groups based on their target proteins. A multi-label classification model was presented to assign drugs into correct target groups. To make full use of the known drug properties, five networks were constructed, each of which represented drug associations in one property. A powerful network embedding method, Mashup, was adopted to extract drug features from above-mentioned networks, based on which several machine learning algorithms, including RAndom k-labELsets (RAKEL) algorithm, Label Powerset (LP) algorithm and Support Vector Machine (SVM), were used to build the classification model. Results and Conclusion: Tenfold cross-validation yielded the accuracy of 0.839, exact match of 0.816 and hamming loss of 0.037, indicating good performance of the model. The contribution of each network was also analyzed. Furthermore, the network model with multiple networks was found to be superior to the one with a single network and classic model, indicating the superiority of the proposed model.

scholarly journals The VIT Transform Approach to Discrete-Time Signals and Linear Time-Varying Systems

Eng ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 99-125
Author(s):  
Edward W. Kamen
Keyword(s):  
Discrete Time ◽  
Initial Conditions ◽  
Linear Time ◽  
Order Term ◽  
Initial Time ◽  
Time Varying ◽  
Varying Coefficients ◽  
Time Signals ◽  
Time Varying Systems ◽  
Time Varying Coefficients

A transform approach based on a variable initial time (VIT) formulation is developed for discrete-time signals and linear time-varying discrete-time systems or digital filters. The VIT transform is a formal power series in z−1, which converts functions given by linear time-varying difference equations into left polynomial fractions with variable coefficients, and with initial conditions incorporated into the framework. It is shown that the transform satisfies a number of properties that are analogous to those of the ordinary z-transform, and that it is possible to do scaling of z−i by time functions, which results in left-fraction forms for the transform of a large class of functions including sinusoids with general time-varying amplitudes and frequencies. Using the extended right Euclidean algorithm in a skew polynomial ring with time-varying coefficients, it is shown that a sum of left polynomial fractions can be written as a single fraction, which results in linear time-varying recursions for the inverse transform of the combined fraction. The extraction of a first-order term from a given polynomial fraction is carried out in terms of the evaluation of zi at time functions. In the application to linear time-varying systems, it is proved that the VIT transform of the system output is equal to the product of the VIT transform of the input and the VIT transform of the unit-pulse response function. For systems given by a time-varying moving average or an autoregressive model, the transform framework is used to determine the steady-state output response resulting from various signal inputs such as the step and cosine functions.

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