Trajectory Optimization for Real-Time Guidance: Part 1, Time-Varying LQR on a Parallel Processor

1990 ◽  
Author(s):  
Mark L. Psiaki ◽  
Kihong Park
Keyword(s):  
Real Time ◽  
Trajectory Optimization ◽  
Time Varying ◽  
Parallel Processor

Real-Time Onboard Trajectory Optimization Using Indirect Methods

2021 ◽  
Author(s):  
Sean M. Nolan ◽  
Clayton A. Smith ◽  
Jacob D. Wood
Keyword(s):  
Real Time ◽  
Trajectory Optimization ◽  
Indirect Methods

Study on real-time thermal–mechanical–frictional coupling characteristics of ball bearings based on the inverse thermal network method

2021 ◽  
pp. 135065012199356
Author(s):  
Tie-Jun Li ◽  
Meng-Zhuo Wang ◽  
Chun-Yu Zhao
Keyword(s):  
Real Time ◽  
Thermal Contact Resistance ◽  
Thermal Contact ◽  
Time Varying ◽  
Ball Bearings ◽  
The Real ◽  
Thermal Network ◽  
Network Method ◽  
Thermal Network Method ◽  
Coupling Characteristics

The real-time thermal–mechanical–frictional coupling characteristics of bearings are critical to the accuracy, reliability, and life of entire machines. To obtain the real-time dynamic characteristics of ball bearings, a novel model to calculate point contact dynamic friction in mixed lubrication was firstly presented in this work. The model of time-varying thermal contact resistance under fit between the ring and the ball, between the ring and the housing, and between the ring and the shaft was established using the fractal theory and the heat transfer theory. Furthermore, an inverse thermal network method with time-varying thermal contact resistance was presented. Using these models, the real-time thermal–mechanical–frictional coupling characteristics of ball bearings were obtained. The effectiveness of the presented models was verified by experiment and comparison.

A New Method for Phase Difference Estimation Based on Time-Varying Signal Model

2013 ◽  
Vol 333-335 ◽  
pp. 650-655
Author(s):  
Peng Hui Niu ◽  
Yin Lei Qin ◽  
Shun Ping Qu ◽  
Yang Lou
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Phase Difference ◽  
Time Signal ◽  
Time Interval ◽  
Time Varying ◽  
Signal Model ◽  
Time Frequency ◽  
Mass Flowmeter ◽  
Coriolis Mass Flowmeter

A new signal processing method for phase difference estimation was proposed based on time-varying signal model, whose frequency, amplitude and phase are time-varying. And then be applied Coriolis mass flowmeter signal. First, a bandpass filtering FIR filter was applied to filter the sensor output signal in order to improve SNR. Then, the signal frequency could be calculated based on short-time frequency estimation. Finally, by short window intercepting, the DTFT algorithm with negative frequency contribution was introduced to calculate the real-time phase difference between two enhanced signals. With the frequency and the phase difference obtained, the time interval of two signals was calculated. Simulation results show that the algorithms studied are efficient. Furthermore, the computation of algorithms studied is simple so that it can be applied to real-time signal processing for Coriolis mass flowmeter.

SCC-100 parallel processor for real-time imaging

1990 ◽  
Author(s):  
William J. Jacobi ◽  
William B. Kendall ◽  
Leo A. Wadsworth
Keyword(s):  
Real Time ◽  
Parallel Processor ◽  
Real Time Imaging

Stability of real-time hybrid simulation involving time-varying delay and direct integration algorithms

2021 ◽  
pp. 107754632110016
Author(s):  
Liang Huang ◽  
Cheng Chen ◽  
Shenjiang Huang ◽  
Jingfeng Wang
Keyword(s):  
Real Time ◽  
Discrete Time ◽  
Continuous Time ◽  
Hybrid Simulation ◽  
Time Varying ◽  
Discrete Time System ◽  
Time System ◽  
Integration Algorithms ◽  
The Stability ◽  
Continuous Time System

Stability presents a critical issue for real-time hybrid simulation. Actuator delay might destabilize the real-time test without proper compensation. Previous research often assumed real-time hybrid simulation as a continuous-time system; however, it is more appropriately treated as a discrete-time system because of application of digital devices and integration algorithms. By using the Lyapunov–Krasovskii theory, this study explores the convoluted effect of integration algorithms and actuator delay on the stability of real-time hybrid simulation. Both theoretical and numerical analysis results demonstrate that (1) the direct integration algorithm is preferably used for real-time hybrid simulation because of its computational efficiency; (2) the stability analysis of real-time hybrid simulation highly depends on actuator delay models, and the actuator model that accounts for time-varying characteristic will lead to more conservative stability; and (3) the integration step is constrained by the algorithm and structural frequencies. Moreover, when the step is small, the stability of the discrete-time system will approach that of the corresponding continuous-time system. The study establishes a bridge between continuous- and discrete-time systems for stability analysis of real-time hybrid simulation.

Slip-Clutch Torque Estimation via Real-Time Adaptive Lookup Table

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Wenpeng Wei ◽  
Hussein Dourra ◽  
Guoming Zhu
Keyword(s):  
Friction Coefficient ◽  
Real Time ◽  
Mean Squared Error ◽  
Surface Friction ◽  
Lookup Table ◽  
Recursive Least Squares ◽  
Time Varying ◽  
Squared Error ◽  
Output Torque ◽  
Clutch Torque

Abstract Transfer case clutch is crucial in determining traction torque distribution between front and rear tires for four-wheel-drive (4WD) vehicles. Estimating time-varying clutch surface friction coefficient is critical for traction torque control since it is proportional to the clutch output torque. As a result, this paper proposes a real-time adaptive lookup table strategy to provide the time-varying clutch surface friction coefficient. Specifically, the clutch-parameter-dependent (such as clutch output torque and clutch touchpoint distance) friction coefficient is first estimated with available low-cost vehicle sensors (such as wheel speed and vehicle acceleration); and then a clutch-parameter-independent approach is developed for clutch friction coefficient through a one-dimensional lookup table. The table nodes are adaptively updated based on a fast recursive least-squares (RLS) algorithm. Furthermore, the effectiveness of adaptive lookup table is demonstrated by comparing the estimated clutch torque from adaptive lookup table with that estimated from vehicle dynamics, which achieves 14.8 Nm absolute mean squared error (AMSE) and 2.66% relative mean squared error (RMSE).

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