• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.3
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• pp.132-138
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• 2011

This paper presents an intelligent control approach for lateral position control of an autonomous four wheel steered snowplowing robotic vehicle. The vehicle is built for removing snow on the highway. Dynamics of the vehicle is derived and linearized for LQR control. Lateral position is controlled by the LQR method first, then the neural network control technique is introduced to improve tracking performances under the presence of load. The feasibility of using four wheel steering control is investigated by simulation studies of lateral position tracking of the Ford F-250 truck model. Performances of a LQR control method and a neural network control method under virtual snowplowing situation are compared.

• Wind and Structures
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• v.15 no.3
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• pp.263-283
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• 2012

This paper presents a framework of nonlinear dynamic analysis of a low-speed moving maglev (magnetically levitated) vehicle subjected to cross winds and controlled using a clipped-LQR actuator with time delay compensation. A four degrees-of-freedom (4-DOFs) maglev-vehicle equipped with an onboard PID (Proportional-Integral-Derivative) controller traveling over guideway girders was developed to regulate the electric current and control voltage. With this maglev-vehicle/guideway model, dynamic interaction analysis of a low-speed maglev vehicle with guideway girders was conducted using an iterative approach. Considering the time-delay issue of unsynchronized tuning forces in control process, a clipped-LQR actuator with time-delay compensation is developed to improve control effectiveness of lateral vibration of the running maglev vehicle in cross winds. Numerical simulations demonstrate that although the lateral response of the maglev vehicle moving in cross winds would be amplified significantly, the present clipped-LQR controller exhibits its control performance in suppressing the lateral vibration of the vehicle.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1014-1019
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• 2005

In this paper, a neural network technique for automatic steering control of a four wheel drive autonomous highway snowplow vehicle is presented. Controllers are designed by the LQR method based on the vehicle model. Then, neural network is used as an auxiliary controller to minimize lateral tracking error under the presence of load. Simulation studies of LQR control and neural network control are conducted for the vehicle model under a virtual snowplowing situation. Tracking performances are also compared for two and four wheeled steering vehicles.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.5
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• pp.165-172
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• 2000

The VDC(Vehicle Dynamic Control) is a control system whose target is to improve stability of a vehicle under lateral motion. A lateral vehicle motion, especially on a slippery road, can lead to a hazardous situation, and the situation can even worsen by the driver`s inappropriate response. In this paper, two VDC systems, a fuzzy-based controller and an LQR-based controller have been developed. The controllers take as input the yaw rate and the sideslip angle of either body or rear wheel, and they yield the direct yaw moment signal by which the vehicle can gain stability during cornering. Simulations have been conducted to evaluate the performance of the control system. The results indicated that the controllers can successfully improve vehicle stability under potentially dangerous driving conditions.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.557-572
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• 2004

Control systems are used to limit structural lateral deflections during large external loads such as winds and earthquakes. Most recently, the semi-active control approach has grown in popularity due to inexpensive control devices that consume little power. As a result, recently designed control systems have employed many semi-active control devices for the control of a structure. In the future, it is envisioned that structural control systems will be large-scale systems defined by high actuation and sensor densities. Decentralized control approaches have been used to control large-scale systems that are too complex for a traditional centralized approach, such as linear quadratic regulation (LQR). This paper describes the derivation of energy market-based control (EMBC), a decentralized approach that models the structural control system as a competitive marketplace. The interaction of free-market buyers and sellers result in an optimal allocation of limited control system resources such as control energy. The Kajima-Shizuoka Building and a 20-story benchmark structure are selected as illustrative examples to be used for comparison of the EMBC and centralized LQR approaches.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.71-76
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• 2008

This paper is concerned with the active vibration control of elevator by means of the active roller guide. To this end, a dynamic model for the horizontal vibration of the elevator consisting of a supporting frame, cage and active roller guides was derived using the energy method. Free vibration analysis was then carried out based on the equations of motion. Active vibration controller was designed based on the equations of motion using the LQR theory and applied to the numerical model. Rail irregularity and wind pressure variation were considered as external disturbance in the numerical simulations. The numerical results show that the active vibration control of elevator is possible.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.3
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• pp.28-35
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• 2003

The objective of the Vehicle Dynamics Control (VDC) system is to maintain vehicle stability under critical lateral motions, It has a good potential of becoming one of the chassis control necessities since the system can be realized with little additional cost on top of the ABS/TCS system, Developed in this research is a hardware-in-the-loop simulator for VDC with a valve control system that modulates the brake pressures at four wheels: Two VDC control logics, a simple control logic and an LQR control logic, have been developed and incorporated in the HILS system. Their performance under various driving conditions was tested in the HILS system and the results are presented.