• Journal of the Korean Institute of Intelligent Systems
• /
• v.10 no.2
• /
• pp.152-160
• /
• 2000

This paper addresses the analysis and design of fuzzy-model-based controller for nonlinear systems using extended PDC and optimal pole-placement schemes. In the design procedure, we represent the nonlinear system using a Takagi-Sugeno fkzy model and formulate the controller rules by using the extended parallel distributed compensator (EPDC) and construct an overall fuzzy logic controller by blending all local state feedback controllers with an optimal pole-placement scheme. Unlike the commonly used parallel distributed compensation technique, by blending a newly extended parallel distributed compensator and the optimal poleplacement schemes, we can design not only a local stable k z y controller but also an overall stable fuzzy controller to perform the tacking control objective. Furthermore, a stability analysis is carried out not only for the fuzzy model but also for a real nonlinear system. Finally. the effectiveness and feasibility of the proposed fizzy model-based controller design method has been shown through a simulation example.

• 제어로봇시스템학회:학술대회논문집
• /
• 1989.10a
• /
• pp.105-108
• /
• 1989

This paper proposes a performance improvement to a control system with state feedback control loops and feedforward control loops proposed in a previous paper. The technique allows to solve the regulator problem and at the same time to make the system follow command signal. The scheme is implemented in a 16 bit microcomputer using a floating coprocessor. Tests on a DC machine have been conducted, comparisons with the previous results are made.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.34-39
• /
• 1991

In this paper, we provide a treatment of the $H^{\infty}$-mixed sensitivity optimization approach to feedback system design. With compromising between the effect of a disturbance at the plant output and the effect of plant perturbations, we propose an algorithm to design robust controller. A $H^{\infty}$-optimization problem is to be equivalent to a Hankel-approximation, this enables the problem to be solved using state-space methods based on balanced realizations.s.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.10
• /
• pp.1-11
• /
• 1996

In this paper, a robust receding horizon control algorithm, which can be employed for a wide class of nonlinear systems with control and state constraints, modeling errors, and disturbances, is considered. In a neighborhood of the origin, a linear feedback controlelr for the linearized system is applied. Outside this neighborhood, a receding horizon control is applied. Robust stability is proved considering the time taken to solve an optimal control problem so that the proposed algorithm can be applied as an on-line controller.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.14 no.2
• /
• pp.155-163
• /
• 1989

For a one link flexible arm control, quadratic optimal control is applied to the dynamic modilling which is derived from an assumed mode method. For the quadratic optimal control technique, the full state feedback must be obtained for closing the control loop, but because some of the states in the flexible system(e.g. the rate of change of the time dependent variables of the mode shapes) can not be directly measured, state estimator is necessary to achieve the practical implementation of the optimal controller. When disturbances and measurement noise occur, stochastic approach must be applied to estimating the states of the system. Kalman Filter is used as a stste estimator. Through the simulation, the flexible system with state estimator is compared with the flexible system assuming that all the states can be measured.

• International Journal of Automotive Technology
• /
• v.7 no.5
• /
• pp.547-554
• /
• 2006

This paper is concerned with an optimal control suspension system using the preview information of road input based on a quarter car model. The main purpose of the control is to combine good vibration isolation characteristics with improved attitude control. The optimal control law is derived with the use of calculus of variation, consisting of three parts. The first part is a full state feedback term that includes integral control acting on the suspension deflection to ensure zero steady-state deflection in response to static body forces and ramp road inputs. The second part is a feed-forward term which compensates for the body forces when they can be detected, and the third part depends on previewed road input. The performance of the suspension is evaluated in terms of frequency domain characteristics and time responses to ramp road input and cornering forces. The effects of each part of the suspension controller on the system behavior are examined.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.495-495
• /
• 2000

The Stewart platform manipulator is a closed-kinematis chain robot manipulator that is capable of providing high st겨ctural rigidity and positional accuracy. However, this is a complex structure, so controllability of the system is not so good. In this paper, it introduces a new robust motion control algorithm using partial state feedback for a class of nonlinear systems in the presence of modelling uncertainties and external disturbances. The major contribution of this work introduces the development and design of robust observer for the slate and the perturbation w.hich is integrated into a variable structure controller(VSC) structure. The combination of controller/observer gives rise to the robust routine called sliding mode control with sliding perturbation observer(SMCSPO). The optimal gains of SMCSPO are easily obtained by genetic algorithm. Simulation and experiment are presented in order to apply to the stewart platform manipulator. There results show highly' accuracy and performance.

• Journal of the Korean Society for Precision Engineering
• /
• v.8 no.3
• /
• pp.64-72
• /
• 1991

This paper deals with the state estimator and controller. All state variables' feedback in the system were used to improve electro hydraulic servo sysem were used to improve electro hydraulic servo system's responese charact- eristics. Many gains of the state variables'and estimator's are produced by the algebraic Riccati equation, and every state variables'optimal gain and estimator gain is selected by trial and error method. For the designed estimator performance's examination, this paper simulate the time response for the step input, the reduced velocity output in subjected to load torque, and the time response for the step input in changing the inertiamoment.

• Journal of Mechanical Science and Technology
• /
• v.18 no.4
• /
• pp.630-639
• /
• 2004

The Stewart platform manipulator is a closed-kinematics chain robot manipulator that is capable of providing high structural rigidity and positional accuracy. However, this is a complex and nonlinear system, so the control performance of the system is not so good. In this paper, a new robust motion control algorithm is proposed. The algorithm uses partial state feedback for a class of nonlinear systems with modeling uncertainties and external disturbances. The major contribution is the design of a robust observer for the state and the perturbation of the Stewart platform, which is combined with a variable structure controller (VSC). The combination of controller and observer provides the robust routine called sliding mode control with sliding perturbation observe. (SMCSPO). The optimal gains of SMCSPO, which is determined by nominal eigenvalues, are easily obtained by genetic algorithm. The proposed fitness function that evaluates the gain optimization is to put sliding function. The control performance of the proposed algorithm is evaluated by the simulation and experiment to apply to the Stewart platform. The results showed high accuracy and good performance.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.26 no.1
• /
• pp.144-149
• /
• 2017

There have been lots of interest on service and entertainment robots. To ensure that robots work in harmony with humans, their stability and compactness are some of the key issues. Obviously, robots with fewer wheels occupy a smaller floor area compared to those with more wheels. In addition, robots with fewer wheels, whose posture stabilities are maintained by feedback control, are stable even under larger accelerations and/or higher locations of the center of mass. To facilitate controller design, it is assumed that both pitch and roll dynamics are decoupled. The dynamic equations of motion for the proposed robot are derived from the Euler-Lagrange equation. To obtain the optimal balancing control law, linear quadratic regulator control methods are applied to the linearized dynamic equations. Simulation and experimental results verify the effectiveness and performance of the proposed balancing control algorithm for a single-wheeled mobile robot.