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Your search keyword '"unbiased minimum variance estimation"' showing total 4 results
Start Over Descriptor "unbiased minimum variance estimation" Topic youla parameterization
4 results on '"unbiased minimum variance estimation"'

1. Estimation of Tire Normal Forces including Suspension Dynamics

Author

Louis Filipozzi, Francis Assadian, Ming Kuang, Rajit Johri, and Jose Velazquez Alcantar

Subjects
normal force estimation, unbiased minimum variance estimation, controller output observer, youla parameterization, Technology
Abstract

Tire normal forces are difficult to measure, but information on the vehicle normal force can be used in many automotive engineering applications, e.g., rollover detection and vehicle and wheel stability. Previous papers use algebraic equations to estimate the tire normal force. In this article, the estimation of tire normal force is formulated as an input estimation problem. Two observers are proposed to solve this problem by using a quarter-car suspension model. First, the Youla Controller Output Observer framework is presented. It converts the estimation problem into a control problem and produces a Youla parameterized controller as observer. Second, a Kalman filter approach is taken and the input estimation problem is addressed with an Unbiased Minimum Variance Filter. Both methods use accelerometer and suspension deflection sensors to determine the vehicle normal force. The design of the observers is validated in simulation and a sensitivity analysis is performed to evaluate their robustness.

Published
2021
Full Text
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2. Advanced Control and Estimation Concepts, and New Hardware Topologies for Future Mobility.

Author

Assadian, Francis F. and Assadian, Francis F.

Subjects
History of engineering & technology, Technology: general issues, 4WD electric vehicle, EHB, EMB, EWB, Youla parameterization, active disturbance rejection control, actuator, adaptive cruise control, air mobility, analysis, application of speed prediction, automated driving, battery aging, bond graph, brake-by-wire, charging management, city bus transport, control, control design, controller output observer, decentralized traction system, deep learning, drift counteraction optimal control, driving force distribution, efficiency optimization, electric vehicle, electric vehicles, electrification, electro-hydraulic brake, electro-mechanical brake, electronic wedge brake, energy efficiency, energy management, energy-saving, equivalent consumption minimization, fuel cell hybrid aircraft, fuel-saving, hardware-in-the-loop experiments, hybrid electric vehicle, hybrid vehicle, independent-wheel drive, lithium ion, macroscopic traffic model, n/a, new energy vehicles, nonlinear optimization, nonlinear system, normal force estimation, optimal control, optimization, passenger comfort, planning, powertrain electrification, robust control, simulation, smooth road feeling, software tool, speed prediction, steering assistance, stochastic optimal control, supercharging, system modeling, traction control, traffic big-data, ultracapacitor, unbiased minimum variance estimation, unresolved issues, vehicle lateral dynamic and control, youla parameterization
Abstract

Summary: According to the National Research Council, the use of embedded systems throughout society could well overtake previous milestones in the information revolution. Mechatronics is the synergistic combination of electronic, mechanical engineering, controls, software and systems engineering in the design of processes and products. Mechatronic systems put "intelligence" into physical systems. Embedded sensors/actuators/processors are integral parts of mechatronic systems. The implementation of mechatronic systems is consistently on the rise. However, manufacturers are working hard to reduce the implementation cost of these systems while trying avoid compromising product quality. One way of addressing these conflicting objectives is through new automatic control methods, virtual sensing/estimation, and new innovative hardware topologies.

3. Estimation of Tire Normal Forces including Suspension Dynamics

Author

Rajit Johri, Ming Kuang, Jose Velazquez Alcantar, Francis Assadian, and Louis Filipozzi

Subjects
Technology, 0209 industrial biotechnology, Control and Optimization, Observer (quantum physics), Computer science, Energy Engineering and Power Technology, 02 engineering and technology, controller output observer, 020901 industrial engineering & automation, Minimum-variance unbiased estimator, 0203 mechanical engineering, unbiased minimum variance estimation, Robustness (computer science), Control theory, Sensitivity (control systems), youla parameterization, Electrical and Electronic Engineering, Suspension (vehicle), Engineering (miscellaneous), Normal force, Renewable Energy, Sustainability and the Environment, 020302 automobile design & engineering, Kalman filter, normal force estimation, Energy (miscellaneous)
Abstract

Tire normal forces are difficult to measure, but information on the vehicle normal force can be used in many automotive engineering applications, e.g., rollover detection and vehicle and wheel stability. Previous papers use algebraic equations to estimate the tire normal force. In this article, the estimation of tire normal force is formulated as an input estimation problem. Two observers are proposed to solve this problem by using a quarter-car suspension model. First, the Youla Controller Output Observer framework is presented. It converts the estimation problem into a control problem and produces a Youla parameterized controller as observer. Second, a Kalman filter approach is taken and the input estimation problem is addressed with an Unbiased Minimum Variance Filter. Both methods use accelerometer and suspension deflection sensors to determine the vehicle normal force. The design of the observers is validated in simulation and a sensitivity analysis is performed to evaluate their robustness.

Published
2021

4. Estimation of Tire Normal Forces including Suspension Dynamics.

Author

Filipozzi, Louis, Assadian, Francis, Kuang, Ming, Johri, Rajit, Velazquez Alcantar, Jose, Yair, Wiseman, and Bellotti, Francesco

Subjects
*PROBLEM solving, *MINIMUM variance estimation, *ALGEBRAIC equations, *KALMAN filtering, *AUTOMOTIVE engineering, *MOTOR vehicle tires
Abstract

Tire normal forces are difficult to measure, but information on the vehicle normal force can be used in many automotive engineering applications, e.g., rollover detection and vehicle and wheel stability. Previous papers use algebraic equations to estimate the tire normal force. In this article, the estimation of tire normal force is formulated as an input estimation problem. Two observers are proposed to solve this problem by using a quarter-car suspension model. First, the Youla Controller Output Observer framework is presented. It converts the estimation problem into a control problem and produces a Youla parameterized controller as observer. Second, a Kalman filter approach is taken and the input estimation problem is addressed with an Unbiased Minimum Variance Filter. Both methods use accelerometer and suspension deflection sensors to determine the vehicle normal force. The design of the observers is validated in simulation and a sensitivity analysis is performed to evaluate their robustness. [ABSTRACT FROM AUTHOR]

Published
2021
Full Text
View/download PDF

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