Dual control theoretic driver assistance - Dynamic characteristics of steering torque control based on linear quadratic regulator

With the purpose of overcoming the defect that unmanned air vehicles (UAVs) are easily disturbed by air current and tend to be unstable, an augmented-stability controller was developed for a certain UAV’s longitudinal motion. According to requirements of short-period damping ratio and control anticipation parameter (CAP) in flight quality specifications of GJB185-86 and C*, linear quadratic regulator (LQR) theory was used in the augmented-stability controller’s design. The simulation results show that the augmented-stability controller not only improves the UAV’s stability and dynamic characteristics but also enhances the UAV’s robustness.

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Torque Control in Brushless DC Motor Using Intelligent Linear Quadratic Regulator Controller

2018 IEEE 7th International Conference on Adaptive Science & Technology (ICAST) ◽

10.1109/icastech.2018.8507030 ◽

2018 ◽

Cited By ~ 1

Author(s):

Tahir A. Zarma ◽

Babagana M. Mustapha ◽

Hussein U. Suleiman ◽

Ahmadu A. Galadima ◽

Evans C. Ashigweke ◽

...

Keyword(s):

Linear Quadratic Regulator ◽

Dc Motor ◽

Torque Control ◽

Brushless Dc Motor ◽

Linear Quadratic ◽

Brushless Dc

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A Mathematical Model of Driver Steering Control Including Neuromuscular Dynamics

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.2837452 ◽

2008 ◽

Vol 130 (3) ◽

Cited By ~ 71

Author(s):

Andrew J. Pick ◽

David J. Cole

Keyword(s):

Path Following ◽

Linear Quadratic Regulator ◽

Driver Model ◽

Steering Wheel ◽

Steering Control ◽

Linear Quadratic ◽

Reflex Action ◽

Path Following Control ◽

Steering Torque ◽

Neuromuscular Dynamics

A mathematical driver model is introduced in order to explain the driver steering behavior observed during successive double lane-change maneuvers. The model consists of a linear quadratic regulator path-following controller coupled to a neuromuscular system (NMS). The NMS generates the steering wheel angle demanded by the path-following controller. The model demonstrates that reflex action and muscle cocontraction improve the steer angle control and thus increase the path-following accuracy. Muscle cocontraction does not have the destabilizing effect of reflex action, but there is an energy cost. A cost function is used to calculate optimum values of cocontraction that are similar to those observed in the experiments. The observed reduction in cocontraction with experience of the vehicle is explained by the driver learning to predict the steering torque feedback. The observed robustness of the path-following control to unexpected changes in steering torque feedback arises from the reflex action and cocontraction stiffness of the NMS. The findings contribute to the understanding of driver-vehicle dynamic interaction. Further work is planned to improve the model; the aim is to enable the optimum design of steering feedback early in the vehicle development process.

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Examination of Different Control Strategies of Heavy-Vehicle Performance

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.2801172 ◽

1996 ◽

Vol 118 (3) ◽

pp. 489-498 ◽

Cited By ~ 15

Author(s):

L. Palkovics ◽

M. El-Gindy

Keyword(s):

Control Strategy ◽

Control Strategies ◽

Linear Quadratic Regulator ◽

Torque Control ◽

Heavy Vehicle ◽

Vehicle Model ◽

Linear Quadratic ◽

Vehicle Performance ◽

Active Steering ◽

Handling Characteristics

Heavy vehicles play an economically important role in the transportation process, and their numbers have been increasing for several decades. The active safety of the highway system is an important consideration in the design of a heavy vehicle combination. In this paper, the handling characteristics of a 5-axle tractor-semitrailer is examined and used to test for the desired features of the vehicle’s handling and stability. Using these results the optimal control criterion is derived for the vehicle. Four different control strategies are examined by using the Linear Quadratic Regulator (LQR) approach. These are, active steering of the rear wheels of the tractor; active steering of the wheels of the trailer; active torque control in the fifth-wheel joint; and active yaw torque acting on the tractor. These controllers are designed and examined using a simplified linear vehicle model. In addition to discussing the above-mentioned approaches, this paper discusses a method of modifying the slip angles at the tractor’s rear (driven) axles, however the yaw torque at the tractor cg also can be controlled using what is called “unilateral braking.” As well, the replacement of the active torque control at the fifth wheel joint, by a control strategy based on the usage of controllable dampers at the fifth-wheel joint, will also be examined. In this case, a nonlinear mathematical model of the vehicle is used and a modified control strategy called the RLQR/H∞ approach is used to ensure the vehicle’s performance in the presence of parametric uncertainties. The examination of these control strategies is conducted by using a sophisticated non-linear vehicle model, and the influence of these control strategies on the vehicle’s directional and roll stability during severe path-follow lane-change manoeuvre is discussed.

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Development of an Autonomous Two-Wheeled Vehicle Robot

Advanced Engineering Forum ◽

10.4028/www.scientific.net/aef.2-3.390 ◽

2011 ◽

Vol 2-3 ◽

pp. 390-395

Author(s):

Minoru Sasaki ◽

Hidenobu Tanaka ◽

Satoshi Ito

Keyword(s):

Control Systems ◽

Integral Method ◽

Linear Quadratic Regulator ◽

Steering Control ◽

Linear Quadratic ◽

Wheeled Vehicle ◽

Roll Rate ◽

Simulation Results ◽

Quadratic Integral ◽

Steering Torque

This paper describes a development of an autonomous two-wheeled vehicle robot. The model of the two-wheeled vehicle using steering control is derived. The control systems are designed by linear quadratic regulator and linear quadratic integral method. Stabilization is achieved by measuring roll angle and roll rate and controlling the steering torque. The experimental results and simulation results show stable running control of the two-wheeled vehicle robot and coincident with each other. The approach is validated through these results.

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Seismic control of damaged structure by pole assignment and intermittent wavelet-based identification

Journal of Vibration and Control ◽

10.1177/10775463211049590 ◽

2021 ◽

pp. 107754632110495

Author(s):

Sahar Golestaneh Zadeh ◽

Majid Amin Afshar

Keyword(s):

Dynamic Characteristics ◽

Near Field ◽

Linear Quadratic Regulator ◽

Pole Assignment ◽

Proportional Integral Derivative ◽

Linear Quadratic ◽

Proportional Integral ◽

Seismic Control ◽

Assignment Method ◽

Control Forces

Calculation of the control forces by control algorithms, such as the pole assignment, proportional-integral-derivative, and linear quadratic regulator, is usually based on initial dynamic characteristics of the intact and undamaged structure, which is considered to be in the ideal conditions. However, because of the effect of natural loads and damage due to aging, these features can change during the structure’s life span, eventually leading to incorrect control forces. In this research, to overcome this problem and to get closer to the actual dynamic characteristics and on the other hand, in order to elude the adverse effects of real-time identification, such as elapsed time of detection, induced to the controller, the intermitted wavelet-based identification technique besides the pole assignment control is introduced. Performance of the proposed controller on three- and five-story with different cases of stiffness and two failure scenarios, under far and near-field earthquakes, are examined and compared by non-updated wavelet-based pole assignment, proportional-integral-derivative and linear quadratic regulator controllers. Results show that damaged structure response controlled by the suggested adapted pole assignment method is significantly reduced compared to ones controlled by other control methods.

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Application of optimal current driver for the torque control of BLDC motor

Archives of Electrical Engineering ◽

10.2478/v10171-011-0014-7 ◽

2011 ◽

Vol 60 (2) ◽

pp. 149-158 ◽

Cited By ~ 2

Author(s):

Jakub Bernat ◽

Sławomir Stępień

Keyword(s):

Feedback Linearization ◽

Fem Analysis ◽

Linear Quadratic Regulator ◽

Torque Control ◽

Brushless Dc Motor ◽

The Novel ◽

Bldc Motor ◽

Linear Quadratic ◽

Brushless Dc ◽

Optimal Current

Application of optimal current driver for the torque control of BLDC motorThis research presents the novel control strategy of the brushless DC motor. The optimal current driver is designed using Linear Quadratic Regulator and feedback linearization. Additionally, the current reshaping strategy is applied to control the motor torque. Thus, the torque controller is built based on the optimal current driver. The motor is simulated using the FEM analysis.

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