• International Journal of Aeronautical and Space Sciences
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• v.6 no.2
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• pp.23-32
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• 2005

An experimental control system is proposed for the attitude control of a simplified 2-DOF helicopter model. The main rotor is a rigid one, and the fuselage is simply supported by a fixed hinge point where the longitudinal motion is decoupled from the lateral one since the translations and the rolling rotation are completely removed. The yaw trim of the helicopter is performed with a tail rotor, by which the azimuthal attitude can be adjusted on the rotatable post in the yaw direction. The robust sliding mode control tracking a given attitude angle is proposed based on the flight dynamics. A pitch damper is inserted for the control of pitching angle while the compensator to reaction torque is used for the control of azimuth angle. Several parameters of the system are selected through experiments. The results shows that the proposed control method effectively counteracts nonlinear perturbations such as main rotor disturbance, undesirable chattering, and high frequency dynamics.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.1006-1013
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• 2011

In this paper, we propose an optimal posture control law for an unmanned bicycle by deriving linear bicycle model from fully nonlinear differential equations. We calculate each equilibrium point of a bicycle under any given turning radius and angular speed of rear wheel. There is only one equilibrium point when a bicycle goes straight, while there are a lot of equilibrium points in case of turning. We present an optimal equilibrium point which makes the leaning input minimum when a bicycle is turning. As human riders give rolling torque by moving center of gravity of a body, many previous studies use a movable mass to move center of gravity like humans do. Instead we propose a propeller as a new leaning input which generates rolling torque. The propeller thrust input makes bicycle model simpler and removes input magnitude constraint unlike a movable mass. The proposed controller can hold optimal equilibrium points using both steering input and leaning input. The simulation results on linear control for circular motion are demonstrated to show the validity of the proposed approach.

• Journal of Power Electronics
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• v.9 no.4
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• pp.654-666
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• 2009

Direct torque control (DTC) of induction machines (IM) is a well-known strategy of these drives control which has a fast dynamic and a good tracking response. In this paper a nonlinear DTC of speed sensorless IM drives is presented which is based on input-output feedback linearization control theory. The IM model includes iron losses using a speed dependent shunt resistance which is determined through some effective experiments. A stator flux vector is estimated through a simple integrator based on stator voltage equations in the stationary frame. A novel method is introduced for DC offset compensation which is a major problem of AC machines, especially at low speeds. Rotor speed is also determined using a rotor flux sliding-mode (SM) observer which is capable of rotor flux space vector and rotor speed simultaneous estimation. In addition, stator and rotor resistances are estimated using a simple but effective recursive least squares (RLS) method combined with the so-called SM observer. The proposed control idea is experimentally implemented in real time using a FPGA board synchronized with a personal computer (PC). Simulation and experimental results are presented to show the capability and validity of the proposed control method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1382-1387
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• 1999

This paper presents an optimal fuzzy power system stabilizer to damp out low frequency oscillation. So far fuzzy controllers have been applied to power system stabilizing controllers due to its excellent properties on the nonlinear systems. But the design process of fuzzy logic power system stabilizer requires empirical and heuristic knowledge of human experts as well as many trial-and-errors in general. This paper presents and optimal design method of the fuzzy logic stabilizer using the genetic algorithm. Non-symmetric membership functions are optimally tuned over an evaluation function. The present inputs of fuzzy stabilizer are torque angle error and the change of torque angle error without loss of generality. The coding method used in this paper is concatenated binary mapping. Each linguistic fuzzy variable, defined as the peak of a membership function, is assigned by the mapping from a minimum value to a maximum value using eight bits. The tournament selection and the elitism are used to keep the worthy individuals in the next generation. The proposed system is applied to the one-machine infinite-bus model of a power system, and the results showed a promising possibility.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.4
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• pp.316-322
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• 2007

The EHA(Electro-hydrostatic Actuator) reveals completely different characteristics from the conventional valve-controlled Electro-hydraulic actuators. In this paper, its mathematical model including nonlinear elements was derived to be verified by experiments. Based on this, a simulation program was developed for the EHAs consisting of an electric motor driven hydraulic pump, pipe lines and a cylinder. The influence of important design parameters such as peak motor torque and rotational inertia moment of the hydraulic pump on control performance was investigated, where the test condition was intentionally selected so that the motor torque was saturated during the transient phase. As a result, design requirements for improving the control accuracy under full speed operation conditions of the EHAs were investigated.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.859-865
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• 2014

Optimization of an electric machine is mainly a nonlinear multi-modal problem. For the optimization of the multi-modal problem, many function calls are required with much consumption of time. To address this problem, this paper proposes a novel hybrid algorithm in which function calls are less than conventional methods. Specifically, the proposed method uses the kriging metamodel and the fill-blank technique to find an approximated solution in a whole problem region. To increase the convergence speed in local peaks, a parallel gradient assisted simplex method is proposed and combined with the kriging meta-model. The correctness and usefulness of the proposed hybrid algorithm is verified through a mathematical test function and applied into the practical optimization as the cogging torque minimization for an interior permanent magnet synchronous machine.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.334-336
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• 1995

An adaptive feedback linearization technique of a PM synchronous motor with specified output dynamic performance is proposed. The adaptive parameter estimation is achieved by a model reference adaptive technique where the stator resistance and flux linkage can be estimated with the current dynamic model and the state observer. Using these estimated parameters, the linearizing control inputs are calculated and a nonlinear coupled model of a PM synchronous motor is input-output linearized. The resultant model has the load torque disturbance. To get ti perfect decoupled model, the load torque is estimated. The adaptation laws are derived by the hyperstability theory and positivity concept. The robustness of the proposed control scheme will be proven through the computer simulations.

• Journal of Magnetics
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• v.16 no.1
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• pp.74-76
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• 2011

Interior permanent-magnet synchronous motors (IPMSMs) produce both magnetic and reluctance torques. The reluctance torque is due to the difference between the d- and q-axis inductances based on the geometric rotor structure. The steady-state performance analysis and precise control of the IPMSMs greatly depend on the accurate determination of the parameters. The three essential parameters of the IPMSMs are the armature flux linkage of the permanent magnet, the d-axis inductance, and the q-axis inductance. In the basic design step of an IPMSM, the inductance parameters are very important for determining the motor characteristics, such as the input voltage, torque, and efficiency. Thus, it is very important to accurately estimate the values of the motor inductances. The inductance parameters of IPMSMs have nonlinear characteristics along the magnet size because the iron core is saturated by the magnet and armature reaction fluxes. In this study, the inductance parameters were calculated using both the magnetic-equivalent-circuit method and the finite-element method (FEM). Then the calculated parameters were compensated by the saturation coefficient function, which was also calculated via the magnetic-equivalent-circuit method and FEM.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.5
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• pp.118-127
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• 1997

In this study, We use microstep control to reduce vibration of step motor. Microstep control of step motor is usually thought of as an extension of conventional step motor control technology. The essence of micro stepping is that we divide the full step of a step motor into a number of substep called microstep and cause the stepmotor to move through a substep per input pulse. In ideal case, by controlling the individual phase currents of a two-phase step motor sinusoidally we can get uniform torque and step angle. But due to the nonlinear characteristics of the step motor, we need to compensate current waveform to improve the over-all smoothness of the conventional micro stepping system. We implement digital Pulse Width Modul- ation (PWM) driver to drive step motor and microphone was used for detecting vibration. Driver enables speed change automatically by increasing or decreasing micro stepping ratio which we call Automatic Switching on the Fly. To compensate the torque harmonics, neural network is applied to the system and we found compensated optimal input current waveform. Finally we can get smooth motion of step motor in a wide range of motor speed.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.2
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• pp.149-157
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• 2001

A nonlinear speed control for a permanent magnet synchronous motor (PMSM) using a simple disturbance estimation technique is presented. By using a feedback linearization scheme, the nonlinear motor model can be linearized in a controllable canonical form, and the desired speed dynamics can be obtained based on the linearized model. This technique, however, gives an undesirable output performance under the mismatch of the system parameters and load conditions. To cancel disturbance by parameter variation, the controller parameters will be estimated by using a disturbance observer theory where the disturbance torque and flux linkage are estimated. since only the two reduced order observers are used for the parameter estimations, the observer designs are considerably simple and the additional load for computation of the controller is negligibly small. The proposed control scheme is implemented on a PMSM using DSP TMS320C31 and the effectiveness is verified through the comparative simulations and experiments.