• Journal of Electrical Engineering and Technology
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• v.11 no.3
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• pp.733-740
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• 2016

To achieve bipedal walking in real human environments, a bipedal robot should be capable of modifiable walking both on uneven terrain with different heights and on flat terrain. In this paper, a novel walking pattern generator based on a 3-D linear inverted pendulum model (LIPM) is proposed to achieve this objective. By adopting a zero moment point (ZMP) variation scheme in real time, it is possible to change the center-of-mass (COM) position and the velocity of the 3-D LIPM throughout the single support phase. Consequently, the proposed method offers the ability to generate a modifiable pattern for walking on uneven terrain without the necessity for any extra footsteps to adjust the COM motion. In addition, a control strategy for bipedal walking on uneven terrain with unknown height is developed. The torques and ground reaction force are measured through force-sensing resisters (FSRs) on each foot and the foot of the robot is modeled as three virtual spring-damper models for the disturbance compensation. The methods for generating the foot and vertical COM of 3-D LIPM trajectories are proposed to achieve modifiable bipedal walking on uneven terrain without any information regarding the height of the terrain. The effectiveness of the proposed method is confirmed through dynamic simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.6
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• pp.555-562
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• 1997

With only the classical PID controller applied to control of a DC motor, good (target) performance characteristic of the controller can be obtained if all the model parameters of DC motor and operating conditions such as external load torque, disturbance, etc. are known exactly. However, in case when some of system parameters or operating conditions are uncertain or unknown, the fixed PID controller does not guarantee good performance, which is assumed with precisely known system parameters and operating conditions. In view of this and the robustness enhancement of DC motor control system, we propose a PID learning controller which consists of a set of learning rules for PID gain tuning and learning of an auxiliary input. The proposed PID learning controller is shown to drive the state of uncertain DC motor system with unknown system parameters and external load torque to the desired one world wide asymptotically. Computer simulation and experimental results are given to demonstrate the effectiveness of the proposed PID learning controller, thereby showing its superiority to the conventional fixed PID controller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2499-2504
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• 2013

Applications of dynamic position control are especially focused on cancellation of unknown disturbance against nonlinear dynamic plants. Control performance is technically dependent upon observation methodology of such disturbance signals. This paper presents a novel control strategy by using linear actuators based on CAN communication networks. Disturbance is measured from placing a ball on a flat plant and image processing technique is applied to observe dynamic position of a ball system. We devise a neural network based PI control system to realize robust control of the dynamic system.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.1
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• pp.51-57
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• 2011

Information of the lateral velocity and the sideslip angle in a vehicle is very useful in many active vehicle safety applications such as yaw stability control and rollover prevention. Because cost-effective sensors to measure the lateral velocity and the sideslip angle are not available, reliable algorithms to estimation them are necessary. In this paper, a sliding mode observer is designed to estimate the lateral velocity. The side slip angle is estimated using the recursive least square with the disturbance observer and the pseudo integral. The estimated parameters from the combined estimation method are updated recursively to minimize the discrepancy between the model and the physical plant, and any possible effects caused by disturbances. The performance of the proposed monitoring system is evaluated through simulations and experiments.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.299-302
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• 1996

A control algorithm is proposed for nonlinear multi-input multi-output(MIMO) batch processes by combining quadratic iterative learning control(Q-ILC) with model predictive control(MPC). Both controls are designed based on output feedback and Kalman filter is incorporated for state estimation. Novelty of the proposed algorithm lies in the facts that, unlike feedback-only control, unknown sustained disturbances which are repeated over batches can be completely rejected and asymptotically perfect tracking is possible for zero random disturbance case even with uncertain process model.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.97-100
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• 1997

A new control method for the robust position control of a brushless DC(BLDC) motor using the asymptotically stable adaptive load torque observer is presented. A precision position control is obtained for the BLDC motor system approximately linearized using the field-orientation method. And the application of the load torque observer is published in [1] using fixed gain. However, the flux linkage is not exactly known for a load torque observer. Therefore, a model reference adaptive observer is considered to overcome the problem of the unknown parameter in this paper. And stability analysis is carried out using Liapunov stability theorem. As a result, asymptotically stable observer gain can be obtained without affecting the overall system response. The load disturbance detected by the asymptotically stable adaptive observer is compensated by feedforwarding the equivalent current having the fast response.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.3
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• pp.240-245
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• 2010

The controller of a model reference adaptive control monitors the plant's inputs and outputs to acknowledge its characteristics. It then adapts itself to the characteristics it encounters instead of behaving in a fixed manner. An important part of every adaptive scheme is the adaptive law for estimating the unknown parameters on line. A more precise model is required to improve performance and to stabilize a given dynamic system, such as a satellite in which performance varies over time and the coefficients change due to disturbances, etc. After model identification, the robust controller ($H{\infty}$) is designed to stabilize the rigid body and flexible body of a satellite, which can be perturbed due to disturbance. The result obtained by the $H{\infty}$ controller is compared with that of the proportional and integration controller which is commonly used for stabilizing a satellite.

• Proceedings of the KIEE Conference
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• 1994.07a
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• pp.389-391
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• 1994

This paper proposes an approach to control the current amplitude and phase simultaneously. To do this, variable structure control and adaptive parameter estimation arc applied to the current control of a single-phase PWM inverter with unknown R-L series load. The load parameters, R and L, are estimated by using the recursive least square method and these parameters are used to adjust the feedback gains of control input. The inverter system is modelled in a 2nd-order system by treating load current variation caused by inductive component as a disturbance. Simulation and experiment based on the 2nd -order model are done and the results show good dynamic response and low THD.

• Journal of Mechanical Science and Technology
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• v.15 no.6
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• pp.720-726
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• 2001

This paper describes a vehicle driving-load estimation method for application to vehicle Intelligent Cruise Control (ICC). Vehicle driving-load consists of aerodynamic force, rolling resistance, and gravitational force due to road slope and is unknown disturbance in a vehicle dynamic model. The vehicle driving-load has been estimated from engine and wheel speed measurements using a vehicle dynamic model a least square method. The estimated driving-load has been used in the adaptation of throttle/brake control law. The performance of the control law has been investigated via both simulation and vehicle tests. The simulation and test results show that the proposed control law can provide satisfactory vehicle-to-vehicle distance control performance for various driving situations.

• Journal of the Korea Institute of Military Science and Technology
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• v.4 no.2
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• pp.157-178
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• 2001

In this paper, the nonlinear control of high precision pointing stabilization system using feedback-linearization design methodology based on system parameter identification is discussed. Modern nonlinear servomechanism theory is adapted to cope with the hard nonlinearities inherent in the turret system. The mathematical models of electrical turret driving system to develop a high performance control algorithm are derived, and the parameter estimation algorithm identifying the unknown system parameters such as vicious and coulomb frictions, stiffness and inertia is developed. Through computer simulation and experiments, it is shown that pointing and tracking accuracy and stabilization against the wideband stochastic disturbance induced by vehicle running on the bump course are improved. Therefore, it is considered the proposed nonlinear control technique is effective in counteracting the nonlinearities and disturbances.