Uk-Youl Huh

Fuzzy model based predictive control

In this paper, the predictive control with the fuzzy model is developed. Predictive control is an effective technique, and the use of a fuzzy model enhances its usefulness for nonlinear processes. The proper fuzzy model is obtained by fuzzy c-means method. Finally, the fuzzy model based predictive control is demonstrated by the nonlinear model with the sensitive dynamics and it is compared with the predictive control with the linear based model.

Stability experiment of a biped walking robot with inverted pendulum

This paper is concerned with a balancing motion formulation and control of the ZMP (zero moment point) for a biped walking robot that has a balancing weight of an inverted pendulum. The original dynamic stability equation of a walking robot is nonlinear; because its balancing weight is an inverted pendulum type. The stabilization equation of a biped walking robot is modeled as a linearized non-homogeneous second order differential equation with boundary conditions. With the FDM (finite difference method) solution of the linearized differential equation, a trajectory of balancing weight can be directly calculated. Furthermore, it makes that possible input the desired ZMP or ZMP trajectory for various gait, situation and complex motion. Also, it can be easily approximated that a balancing range or motion when some link parameters are changed; especially a balancing mass is changed. In this paper, the simulator with a balancing weight of an inverted pendulum is programmed to get and calculate the desired ZMP and the actual ZMP. The operating program is developed for a real biped walking robot IWRIII-IP. Walking of 6 steps will be simulated and experimented with a real biped walking robot. This balancing system will be applied to a biped humanoid robot, which consist legs and upper body, at future work.

A G2 Continuous Path-smoothing Algorithm Using Modified Quadratic Polynomial Interpolation

Path searching algorithm is one of the main topics in studies on path planning. These algorithms are used to avoiding obstacles and find paths from starting point to target point. There are dynamic problems that must be addressed when these paths are applied in real environments. In order to be applicable in actual situations, the path must be a smooth path. A smooth path is a path that maintains continuity. Continuity is decided by the differential values of the path. In order to be G2 continuous, the secondary differential values of the path must be connected throughout the path. In this paper, the interpolation method is used to construct continuous paths. The quadratic polynomial interpolation is a simple method for obtaining continuous paths about three points. The proposed algorithm makes a connection of three points with curves and the proposed path is rotated using the parametric method in order to make the path optimal and smooth. The polynomials expand to the next three points and they merge into the entire path using the membership functions with G2 continuity.

An error feedback model based adaptive controller for nonlinear systems

In this paper, a method of designing an adaptive controller is proposed to solve some problems in model reference adaptive control (MRAC) for nonlinear plants. The MRAC was originally designed for the unknown plant which should be linear and completely disturbance free. Practically, since real plants have nonlinearities, such as disturbances and unmodelled dynamics, the performance of the controller is worsened. This paper describes an error feedback model which is a reference model with the output error feedback, for improving robustness and stability to nonlinear characteristics. The proposed model can be used for MRAC using the measurable output of the plant and the states of the proposed model. Experiments on an SR (switched reluctance) motor have been done in order to illustrate the validity of the proposed controller.

MIMO fuzzy model for boiler-turbine systems

We design a MIMO fuzzy model for boiler-turbine systems which has highly nonlinear dynamics. It is necessary to linearize the boiler-turbine system at every operating point for linear modeling. Also, as it is going to be a high order model, the linearization method has many constraints due to the complexity of the boiler-turbine system. This paper shows that fuzzy modeling is a very simple approach to highly nonlinear systems. Results of fuzzy modeling are presented.

A modified sliding mode speed control scheme for AC servo motor

In this paper, a sliding mode controller (SMC) which can be characterized by high accuracy, fast response and robustness is applied to speed control of an AC-servo motor. The control input is changed to a continuous one in the boundary layer to reduce the chattering phenomenon, and the boundary layer converges to zero when the state variables of the system reach their steady state values. The integral compensator is added to reduce steady state error and to provide the continuous torque reference. The acceleration which is necessary to get the sliding plane is estimated by an observer. The sliding surface is included in the control input to enhance the robustness and transient response without increasing the sliding mode controller gain. The proposed controller is implemented by DSP (digital signal processor). The effectiveness of the proposed control scheme for the speed controller is confirmed through the real-time experimental results in the paper.

Fuzzy logic based switching angle controller for SR motor speed control

The paper describes a switching angle controller for speed control of switched reluctance motor (SRM). The speed of the SRM can be controlled by phase currents and switching angles. It is difficult to achieve the desired dynamic performances because the developed torque is not proportional to the switching angle. Fuzzy control provides a good approach to the nonlinear system because it does not require mathematical models to formulate the control algorithm. This paper proposes a switching angle controller with fuzzy rules for the high speed control of the SRM. The switching angle controller is developed by a simple adaptive scheme and its fuzzy rule bases are generated by a Lyapunov function. We show that the proposed controller with fuzzy logic has good performance for the nonlinear SRM in experiments.

Fuzzy logic control for the contouring accuracy of XY positioning system

In this paper, we propose a fuzzy logic controller for XY positioning system. In motion control, the major sources of uncertainties are friction, inertia, stiffness and disturbances. These uncertainties should be taken into account by any high performance robust motion controller. A cross coupled controller utilizes all axis position error information simultaneously to produce accurate contours. However, the existing cross coupled controllers cannot overcome friction, backlash and parameter variation. Also, since it is difficult to obtain an accurate mathematical model of the XY system, we investigate a fuzzy logic cross coupled controller of an XY positioning system. The overall control system consists of three parts, the position controller, the speed controller, the fuzzy logic controller. New contour error vector computation method is also presented. The performance of the proposed controller is shown to be effectiveness through some simulations and experiments.

Improved contouring control for multi-axis system with two-degrees-of-freedom structure

This paper represents a position controller with a disturbance observer for a multi-axis servo system. The overall control system consists of three parts: the position controller; the disturbance observer with free parameters; and the cross-coupled controller which enhances contouring performance by reducing errors. Using two-degrees-of freedom conception, the authors design the command input response and the closed loop characteristics independently. The servo system can improve the closed loop characteristics without affecting the command input response. The characteristics of the closed loop system is improved by suppressing disturbance torque effectively with the disturbance observer. Moreover, the cross-coupled controller enhances tracking performance. Thus position control performance is improved. Finally, the performance of the proposed controller shows that it improves the contouring performance along with reference trajectory in the XY-table.

Re-adhesion control with estimated adhesion force coefficient for wheeled robot using fuzzy logic

Mobility of an indoor wheeled robot is affected by adhesion force that is related to various floor conditions. When the adhesion force between driving wheels and the floor decreases suddenly, the robot has a slip state. First of all, this paper is applied by adhesion characteristics and slip in wheeled robot. Secondly, the paper proposes estimation method of adhesion force coefficient (AFC) according to slip velocity. In order to overcome this slip problem, optimal slip velocity must be decided for stable movement of wheeled robot. The paper proposes a re-adhesion control system based on an ordinary disturbance observer, that is, the re-adhesion control is achieved by reducing the driving torque enough to give maximum AFC. In additionally, this algorithm controls recovered driving torque for the restrain the re-slip. Fuzzy logic control (FLC) is pretty useful with prevention of the slip phenomena through that compare fuzzy with PI control for the controller performance in the re-adhesion control strategy. For the configuration of fuzzy sets, proposed algorithm applied by the Takagi-Sugeno model. These procedures are implemented using a Pioneer 2-DXE parameter.