• Journal of Electrical Engineering and Technology
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• v.7 no.4
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• pp.513-523
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• 2012

For precisely regulating the speed of a permanent magnet synchronous motor system with unknown load torque disturbance and disturbance inputs, an LMI-based sliding mode control scheme is proposed in this paper. After a brief review of the PMSM mathematical model, the sliding mode control law is designed in terms of linear matrix inequalities (LMIs). By adding an extended observer which estimates the unknown load torque, the proposed speed tracking controller can guarantee a good control performance. The stability of the proposed control system is proven through the reachability condition and an approximate method to implement the chattering reduction is also presented. The proposed control algorithm is implemented by using a digital signal processor (DSP) TMS320F28335. The simulation and experimental results verify that the proposed methodology achieves a more robust performance and a faster dynamic response than the conventional linear PI control method in the presence of PMSM parameter uncertainties and unknown external noises.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.2
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• pp.278-294
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• 2015

Considering the guidance and control problem of the near space interceptor (NSI) during the terminal course, this paper proposes a three-channel independent integrated guidance and control (IGC) scheme based on the backstepping sliding mode and finite time disturbance observer (FTDO). Initially, the three-channel independent IGC model is constructed based on the interceptor-target relative motion and nonlinear dynamic model of the interceptor, in which the channel coupling term and external disturbance are regarded as the total disturbances of the corresponding channel. Then, the FTDO is introduced to estimate the target acceleration and control system loop disturbances, and the feed-forward compensation term based on the estimated values is employed to effectively remove the effect of disturbances in finite time. Subsequently, the IGC algorithm based on the backstepping sliding mode is also given to obtain the virtual control moment. Furthermore, a robust least-squares weighted control allocation (RLSWCA) algorithm is employed to distribute the previous virtual control moment among the corresponding aerodynamic fins and reaction jets, which also takes into account the uncertainty in the control effectiveness matrix. Finally, simulation results show that the proposed IGC method can obtain the small miss distance and smooth interceptor trajectories.

• International Journal of Automotive Technology
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• v.5 no.2
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• pp.135-144
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• 2004

In this paper, the model-matching control in the longitudinal autonomous driving system is investigated by vehicle dynamics simulation, which contains nonlinear subcomponents and simplified subcomponents. The design of the robust model-matching controller is performed by the characteristics of the 2 degrees of freedom controller, which is composed of the feedforward compensator and the feedback compensator. It makes the characteristics of tractive and brake force to be equivalent to the specific transfer function, which is suggested as the reference model. Mathematical models of vehicle dynamic analysis including the model-matching control are constructed for computer simulation. Then, simple examples on open-loop simulation without any controller and closed loop simulation with the model-matching controller are applied to check the validity of the robust controller. As the practical example, the autonomous driving system in the longitudinal direction is adopted. It is proved that the model-matching control is effective and adequate to the disturbances and the perturbations, which are shown in the responses of the change of a vehicle mass and a road gradient.

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.255-260
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• 2008

In the recently years, there has been a big interest in ad hoc wireless network as they have tremendous military and commercial potential. An Ad hoc wireless network is composed of mobile computing devices that use having no fixed infrastructure of a multi-hop wireless network formed. So, the fact that limited resource could support the network of robust, simple framework and energy conserving etc. In this paper, we propose a new ad hoc multicast routing protocol for based on the ontology scheme called inference network. Ontology knowledge-based is one of the structure of context-aware. And the ontology clustering adopts a tree structure to enhance resilient against mobility and routing complexity. This proposed multicast routing protocol utilizes node locality to be improve the flexible connectivity and stable mobility on local discovery routing and flooding discovery routing. Also attempts to improve route recovery efficiency and reduce data transmissions of context-awareness. We also provide simulation results to validate the model complexity. We have developed that proposed an algorithm have design multi-hierarchy layered networks to simulate a desired system.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.117-123
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• 2001

To improve control performance of a non-linear system, many other reserches have used the sliding model control algorithm. The sliding mode controller is known to be robust against nonlinear and unmodeled dynamic terms. However, this algorithm raises the inherent chattering caused by excessive switching inputs around the sliding surface. Therefore, in order to solve the chattering problem and improve control performance, this study has developed the sliding mode controller with a perturbation estimator using the observer-based fuzzy adaptive network. The perturbation estimator based on the fuzzy adaptive network generates the control input of compensating unmodeled dynamics terms and disturbance. And the weighting parameters of the fuzzy adaptive network are updated on-line by adaptive law in order to force the estimation errors converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluation control performance of the proposed approach, tracking control simulation is carried is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.22-28
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• 2014

This paper proposes the fuzzy modeling and robust stability analysis of wind farm based on prediction model for wind speed. Owing to the sensitivity of wind speed, it is necessary to study the dynamic equation of the variable speed wind turbine. In this paper, based on the least-square method, the wind speed prediction model which is varied by the surrounding environment is proposed so that it is possible to evaluate the practicability of our model. And, we propose the composition of intelligent wind farm and use the fuzzy model which is suitable for the design of fuzzy controller. Finally, simulation results for wind farm which is modeled mathematically are demonstrated to visualize the feasibility of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.506-506
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• 2000

To improve control performance of a non-linear system, many other researches have used the sliding mode control algorithm. The sliding mode controller is known to be robust against nonlinear and unmodeled dynamic terms. However. this algorithm raises the inherent chattering caused by excessive switching inputs around the sliding surface. Therefore, in order to solve the chattering problem and improve control performance, this study has developed the sliding mode controller with a perturbation estimator using the observer-based fuzzy adaptive network generates the control input for compensating unmodeled dynamics terms and disturbance. And, the weighting parameters of the fuzzy adaptive network are updated on-line by adaptive law in order to force the estimation errors to converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluating control performance of the proposed approach. tracking control simulation is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.651-659
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• 2002

Component Mode Synthesis (CMS) is a dynamic substructuring technique to get an approximate eigensolutions of large degree-of-freedom structures divisible into several components. But, In practice. most of large structures are modeled by different teams of engineers. and their respective finite element models often require different mesh resolutions. As a result, the finite element substructure models can be non-conforming and/or incompatible. In this work, A hybrid version of component mode synthesis using a localized lagrange multiplier to treat the non-conforming mesh problem was derived. Evolution Strategies (ESs) is a stochastic numerical optimization technique and has shown a robust performance for solving deterministic problems. An ESs conducts its search by processing a population of solutions for an optimization problem based on principles from natural evolution. An optimization example for raising the first natural frequency of a plate structure using beam stiffeners was presented using hybrid component mode synthesis and robust evolution strategies (RES) optimization technique. In the example. the design variables are the positions and lengths of beam stiffeners.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.217-221
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• 2007

This paper deals with the robust nonlinear controller design using output feedback for a Chua circuit which is one of the well-known nonlinear models. First, an exosystem for reference signal tracking is defined, and error dynamic equations are derived from the differentiation of the output tracking error equation. The normal sliding surface is modified using the integral type servo compensator. The parameters in the equations of the modified sliding surface and servo compensator are determined by using the Hurwitz condition of stability. Especially the error signals can't be obtained directly from the output because all parameters are assumed unknown. So instead, a high gain observer is designed. From this estimated error signals, a stabilizing controller is designed. Simulation is done for demonstrating the effectiveness of the suggested algorithm.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.4
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• pp.259-266
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• 2015

This study presents new scheme for various walking pattern of biped robot under the limitted enviroments. We show that the neural network is significantly more attractive intelligent controller design than previous traditional forms of control systems. A multilayer backpropagation neural network identification is simulated to obtain a learning control solution of biped robot. Once the neural network has learned, the other neural network control is designed for various trajectory tracking control with same learning-base. The main advantage of our scheme is that we do not require any knowledge about the system dynamic and nonlinear characteristic, and can therefore treat the robot as a black box. It is also shown that the neural network is a powerful control theory for various trajectory tracking control of biped robot with same learning-vase. That is, we do net change the control parameter for various trajectory tracking control. Simulation and experimental result show that the neural network is practically feasible and realizable for iterative learning control of biped robot.