• Advances in aircraft and spacecraft science
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• v.7 no.6
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• pp.553-570
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• 2020

To address the problems caused by the strong coupling of an airbreathing hypersonic vehicle's airframe and propulsion to the integrated control system design, an integrated airframe-propulsion model is established, and the coupling characteristics between the aircraft and engine are analyzed. First, the airframe-propulsion integration model is established based on the typical nonlinear longitudinal dynamical model of an air-breathing hypersonic vehicle and the one-dimensional dual-mode scramjet model. Thrust, moment, angle of attack, altitude, and velocity are used as transfer variables between the aircraft model and the engine model. The one-dimensional scramjet model can accurately reflect the working state of the engine and provide data to support the coupling analysis. Second, owing to the static instability of the aircraft model, the linear quadratic regulator (LQR) controller of the aircraft is designed to ensure attitude stability and height tracking. Finally, the coupling relationship between the aircraft and the engine is revealed through simulation examples. The interaction between vehicle attitude and engine working condition is analyzed, and the influence of vehicle attitude on engine safety is considered. When the engine is in a critical working state, the attitude change of the aircraft will not affect the engine safety without considering coupling, whereas when coupling is considered, the attitude change of the aircraft may cause the engine unstart, which demonstrates the significance of considering coupling characteristics.

• Journal of Astronomy and Space Sciences
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• v.14 no.1
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• pp.142-149
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• 1997

This paper applied one of the well-known optimal control theory, namely, linear quadratic regulator(LQR), to the station-keeping maneuvers(SKM) for a geostationary satellite. The boundary conditions to transfer the system with a good accuracy at a terminal time were based upon the predicted orbital data which are created due to the Earth's non-uniform mass distribution's effect during 14 days and due to luni-solar effect during 28 days. Through the linearization of the nonlinear system equation with respect to reference orbit and the numerical integration of Riccati equation, the optimal trajectories and the corresponding control law have been obtained by using LQR. From the comparison of ${\Delta}V$ obtained by LQR with the ${\Delta}V$ obtained anatically by geometric method, Station Keeping Maneuvers(SKM) via LQR may provide comparable results to a real system. Furthermore it will demonstrate the possibility in fuel optimization and life extension of geostationary satellite.

• Nuclear Engineering and Technology
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• v.21 no.2
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• pp.99-110
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• 1989

The optimal control of xenon concentration in a nuclear reactor is posed as a linear quadratic regulator problem with state feedback control. Since it is not possible to measure the state variables such as xenon and iodine concentrations directly, implementation of the optimal state feedback control law requires estimation of the unmeasurable state variables. The estimation method used is based on the Luenberger observer. The set of the reactor kinetics equations is a stiff system. This singularly perturbed system arises from the interaction of slow dynamic modes (iodine and xenon concentrations) and fast dynamic modes (neutron flux, fuel and coolant temperatures). The singular perturbation technique is used to overcome this stiffness problem. The observer-based controller of the original system is effected by separate design of the observer and controller of the reduced subsystem and the fast subsystem. In particular, since in the reactor kinetics control problem analyzed in the study the fast mode dies out quickly, we need only design the observer for the reduced slow subsystem. The results of the test problems demonstrated that the state feedback control of the xenon oscillation can be accomplished efficiently and without sacrificing accuracy by using the observer combined with the singular perturbation method.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.338-340
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• 1993

In this paper, the method for designing a robust linear multivariable model following servo system is proposed. This model following servo system for the (n)th order reference input and the (n)th order disturbance is treated, and is designed so that the (n)th order response of the plant should be kept close to the (n)th order response of the given model by LQ(Linear Quadratic) optimal regulator approach. It is proved that the characteristics of the model following servo system is robust in the presence of the disturbances and the parameter perturbations of the plant dynamics.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1080-1085
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• 2005

A hybrid control scheme is proposed for the stabilization of backward movement along simple paths for a vehicle composed of a truck and six trailers. The hybrid comprises the combination of a linear quadratic regulator (LQR) and a neurocontroller (NC) that is trained by a genetic algorithm (GA). Acting singly, either the NC or the LQR are unable to perform satisfactorily over the entire range of the operation required, but the proposed hybrid is shown to be capable of providing good overall system performance. The evaluation function of the NC in the hybrid design has been modified from the conventional type to incorporate both the squared errors and the running steps errors. The reverse movement of the trailer-truck system can be modeled as an unstable nonlinear system, with the control problem focusing on the steering angle. Achieving good backward movement is difficult because of the restraints of physical angular limitations. Due to these constraints the system is impossible to globally stabilize with standard smooth control techniques, since some initial states necessarily lead to jack-knife locks. This paper demonstrates that a hybrid of neural networks and LQR can be used effectively for the control of nonlinear dynamical systems. Results from simulated trials are reported.

• Journal of Power Electronics
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• v.8 no.1
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• pp.10-22
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• 2008

The wind-driven doubly fed induction generator (DFIG) is currently under pressure to be more grid-compatible. The main concern is the fault ride-through (FRT) requirement to keep the generator connected to the grid during faults. In response to this, the paper introduces a novel model and new control scheme for the DFIG. The model provides a means of direct stator power control and considers the stator transients. On the basis of the derived model, a robust linear quadratic (LQ) controller is synthesized. The control law has proportional and integral actions and takes account of one sample delay in the input owing to the microprocessor's execution time. Further, the influence of the grid voltage imperfection is mitigated using frequency shaped cost functional method. Compensation of the rotor current pulsations is proposed to improve the FRT capability as well as the generator performance under grid voltage unbalance. As a consequence, the control system can achieve i) fast direct power control without instability risk, ii) alleviation of the problems associated with the DFIG operation under unbalanced grid voltage, and iii) high probability of successful grid FRT. The effectiveness of the proposed solution is confirmed through simulation studies on 2MW DFIG.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.12
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• pp.1330-1337
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• 2004

In this study, the equations of motion of a rigid rotor supported by magnetic bearings are derived via Hamilton's principle, and transformed to a state-space form for control purpose. The optimal motion control of rotor magnetic bearing system based on the LQR(linear quadratic regulator) theory is addressed. New schemes related to the selection of the state weighting matrix Q and the control weighting matrix R involved in the quadratic functional to be minimized are proposed. And the robust control of the system with an LMI(linear matrix inequality) based H$_{\infty}$ theory is dealt with in this paper. Loop shapings of TFM (transfer function matrix) are used to increase the performance of control capability of the system. The control abilities of LQR and H$_{\infty}$ controller are compared by simulation and experimental tests and show that the capability of H$_{\infty}$ controller is superior to that of LQR.

• Journal of Power Electronics
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• v.11 no.4
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• pp.393-400
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• 2011

The main objective of this paper is to control the speed of Nonlinear Hybrid Electric Vehicle (HEV) by controlling the throttle position. Various control techniques such as well known Proportional-Integral-Derivative (PID) controller in conjunction with state feedback controller (SFC) such as Pole Placement Technique (PPT), Observer Based Controller (OBC) and Linear Quadratic Regulator (LQR) Controller are designed. Some Intelligent control techniques e.g. fuzzy logic PD, Fuzzy logic PI along with Adaptive Controller such as Self Organizing Controller (SOC) is also designed. The design objective in this research paper is to provide smooth throttle movement, zero steady-state speed error, and to maintain a Selected Vehicle (SV) speed. A comparative study is carried out in order to identify the superiority of optimal control technique so as to get improved fuel economy, reduced pollution, improved driving safety and reduced manufacturing costs.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.3
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• pp.209-217
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• 2001

In this paper, we propose a linear quadratic regulator(LQR) controller design for the active suspension using evolution strategy(ES) and neural network. We can improve the inherent suspension problem, the trade-off between ride quality and suspension travel by selecting appropriate weight in the LQR-objective function. Since any definite rules for selecting weights do not exist, we replace the designers trial-and-error method with ES that is an optimization algorithm. Using the ES, we can find the proper control gains for selected frequencies, which have major effects on the vibrations of the vehicle. The relationship between the frequencies and proper control gains are generalized by use of the neural networks. When the vehicle is driven, the trained neural network is activated and provides the proper gains for operating frequencies. And we adopted double sky-hook control to protect car component when passing large bump. Effectiveness of our design has been shown compared to the conventional sky-hook controller through simulation studies.

• Nuclear Engineering and Technology
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• v.26 no.4
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• pp.536-547
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• 1994

The state feedback optimal control techniques are used in designing the reactor control system. The mathematical plant model with the temperature feedback effects is established from the one delayed neutron group point kinetics equation and the singly lumped thermal-hydraulic balance equations, and is expressed in terms of state variables. The LQR (Linear Quadratic Regulator) control system is designed, being followed by the LQG (Linear Quadratic Gaussian) design to determine the optimal conditions of rod movement for the desired reactor power responses. And two different servo control schemes, the ordinary feedback system and the order increased regulating system, are proposed for the purpose of input tacking. The general control characteristics such as stability margins and output responses are discussed. Comparing each other, it is found that the order increased regulating system has far better control characteristics than the ordinary feedback system.