• International Journal of Aeronautical and Space Sciences
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• 제8권1호
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• pp.10-20
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• 2007

For spacecraft attitude control, reaction wheel (RW) steering laws with more than three wheels for three-axis attitude control can be derived by using a control allocation (CA) approach.1-2 The CA technique deals with a problem of distributing a given control demand to available sets of actuators.3-4 There are many references for CA with applications to aerospace systems. For spacecraft, the control torque command for three body-fixed reference frames can be constructed by a combination of multiple wheels, usually four-wheel pyramid sets. Multi-wheel configurations can be exploited to satisfy a body-axis control torque requirement while satisfying objectives such as minimum control energy.1-2 In general, the reaction wheel steering laws determine required torque command for each wheel in the form of matrix pseudo-inverse. In general, the attitude control command is generated in the form of a feedback control. The spacecraft body angular rate measured by gyros is used to estimate angular displacement also.⁵ Combination of the body angular rate and attitude parameters such as quaternion and MRPs(Modified Rodrigues Parameters) is typically used in synthesizing the control command which should be produced by RWs.¹ The attitude sensor signals are usually corrupted by noise; gyros tend to contain errors such as drift and random noise. The attitude determination system can estimate such errors, and provide best true signals for feedback control.⁶ Even if the attitude determination system, for instance, sophisticated algorithm such as the EKF(Extended Kalman Filter) algorithm⁶, can eliminate the errors efficiently, it is quite probable that the control command still contains noise sources. The noise and/or other high frequency components in the control command would cause the wheel speed to change in an undesirable manner. The closed-loop system, governed by the feedback control law, is also directly affected by the noise due to imperfect sensor characteristics. The noise components in the sensor signal should be mitigated so that the control command is isolated from the noise effect. This can be done by adding a filter to the sensor output or preventing rapid change in the control command. Dynamic control allocation(DCA), recently studied by Härkegård, is to distribute the control command in the sense of dynamics⁴: the allocation is made over a certain time interval, not a fixed time instant. The dynamic behavior of the control command is taken into account in the course of distributing the control command. Not only the control command requirement, but also variation of the control command over a sampling interval is included in the performance criterion to be optimized. The result is a control command in the form of a finite difference equation over the given time interval.⁴ It results in a filter dynamics by taking the previous control command into account for the synthesis of current control command. Stability of the proposed dynamic control allocation (CA) approach was proved to ensure the control command is bounded at the steady-state. In this study, we extended the results presented in Ref. 4 by adding a two-step dynamic CA term in deriving the control allocation law. Also, the strict equality constraint, between the virtual and actual control inputs, is relaxed in order to construct control command with a smooth profile. The proposed DCA technique is applied to a spacecraft attitude control problem. The sensor noise and/or irregular signals, which are existent in most of spacecraft attitude sensors, can be handled effectively by the proposed approach.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2009년도 춘계학술대회 논문집
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• pp.654-655
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• 2009

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2010년도 춘계학술대회 논문집
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• pp.714-715
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• 2010

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2010년도 춘계학술대회 논문집
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• pp.708-709
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• 2010

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2011년도 춘계학술대회 논문집
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• pp.300-301
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• 2011

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2011년도 춘계학술대회 논문집
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• pp.490-491
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• 2011

• 한국우주과학회:학술대회논문집(한국우주과학회보)
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• 한국우주과학회 2004년도 한국우주과학회보 제13권2호
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• pp.103-103
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• 2004

• 제어로봇시스템학회논문지
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• 제20권5호
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• pp.551-556
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• 2014

This paper proposes a balancing control and driving control of a bicycle robot based on dynamic modeling of the bicycle robot, which has been derived using the Lagrange equations. For the balancing control of the bicycle robot, a reaction wheel pendulum method has been adopted in this research. By using the dynamics equations of the bicycle robot, an LQR controller has been designed for a balancing and driving control of a bicycle robot. The performance of the balance control is verified experimentally before the driving control, which shows a stable posture within one degree vibrations. To show the dynamic characteristics of the bicycle robot during driving, a trapezoidal velocity trajectory is selected as the references. Through simulations and real experiments, the effectiveness of the proposed algorithm has been demonstrated.

• 제어로봇시스템학회논문지
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• 제18권6호
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• pp.532-539
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• 2012

This paper proposes a balancing and driving control system for a bicycle robot. A reaction wheel pendulum control method is adopted to maintain the balance while the bicycle robot is driving. For the driving control, PID control algorithm with a variable gain adjustment has been developed in this paper, where the gains are heuristically adjusted during the experiments. To measure the angles of the wheels the encoders are used. For the balancing control, a roll controller is designed with a non-model based algorithm to make the shortest cycle. The tilt angle is measured by the fusion of the acceleration and gyroscope sensors, which is used to generate the control input of the roll controller to make the tilt angle zero. The performance of the designed control system has been verified through the real experiments with the developed bicycle robot.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 추계학술대회 논문집
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• pp.283-290
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• 2007

A bi-modal tram has been developed to offer an advanced transportation service compared with existing vehicles. The All-Wheel-Steering system is applied to the bi-modal tram to satisfy the required steering performance because the bi-modal tram has extended length and articulated mechanism. An ECU for the steering system is essential to steer wheels on 2nd and 3rd axles by the specific AWS algorithm with the prescribed driving condition. The Hardware-In-the-Loop Simulation(HILS) system is planned for the purpose of evaluating the steering system of the bi-modal tram. There are kinematic links with the hydraulic actuator to steer wheels on each 2nd and 3rd axles and also same steering mechanism as the actual vehicle is in the HILS system. Controlling the movement of hydraulic actuator which reflects the lateral steering reaction force on each wheel is the key to realize the HILS system, but the reaction force is continuously changed according to various driving conditions. Therefore, the simulation through the multi-body dynamics model is used to obtain the required forces.