Chae-Joo Moon

Direct adaptive self-structuring fuzzy controller for nonaffine nonlinear system

A direct adaptive state-feedback controller for highly nonlinear systems is proposed. This paper considers uncertain or ill-defined nonaffine nonlinear systems and employ a static fuzzy logic system (FLS) with an on-line structuring algorithm. The FLS approximates and adaptively cancels an unknown plant nonlinearity. A control law and adaptive laws for unknown fuzzy parameters and bounding constant are established so that the whole closed-loop system is stable in the sense of Lyapunov. The tracking error is guaranteed to be uniformly asymptotically stable rather than uniformly ultimately bounded with the aid of an additional robustifying control term. No a priori knowledge of an upper bound on an lumped uncertainty is required.

Adaptive Neural Control for Strict-Feedback Nonlinear Systems Without Backstepping

In this brief, a new adaptive neurocontrol algorithm for a single-input-single-output (SISO) strict-feedback nonlinear system is proposed. Most of the previous adaptive neural control algorithms for strict-feedback nonlinear systems were based on the backstepping scheme, which makes the control law and stability analysis very complicated. The main contribution of the proposed method is that it demonstrates that the state-feedback control of the strict-feedback system can be viewed as the output-feedback control problem of the system in the normal form. As a result, the proposed control algorithm is considerably simpler than the previous ones based on backstepping. Depending heavily on the universal approximation property of the neural network (NN), only one NN is employed to approximate the lumped uncertain system nonlinearity. The Lyapunov stability of the NN weights and filtered tracking error is guaranteed in the semiglobal sense.

Output-feedback control of uncertain nonlinear systems using a self-structuring adaptive fuzzy observer

This paper describes the design of an output-feedback controller based on an adaptive fuzzy observer for uncertain single-input, single-output nonlinear dynamical systems. We have focused on the realization of a minimal dynamic order for the adaptive fuzzy observer. For this purpose, we adopt an adaptive fuzzy observer in which no strictly positive real (SPR) condition is needed and we combine a self-structuring scheme with an on-line estimation of fuzzy parameters. By using this proposed scheme, we can reduce the dynamic order of the adaptive output-feedback fuzzy control system. The Lyapunov synthesis approach is used to guarantee a global uniform ultimate boundedness property of the state estimation error and tracking error, as well as all other signals in the closed-loop system. No a priori knowledge of an upper limits on the uncertainties including optimal parameters and modeling errors is required. The theoretical results are illustrated through simulation examples.

Embedded Switched-Inductor Z-Source Inverters

In this paper, a ripple input current embedded switched-inductor Z-source inverter (rESL-ZSI) and a continuous input current embedded switched-inductor Z-source inverter (cESL-ZSI) are proposed by inserting two dc sources into the switched-inductor cells. The proposed inverters provide a high boost voltage inversion ability, a lower voltage stress across the active switching devices, a continuous input current and a reduced voltage stress on the capacitors. In addition, they can suppress the startup inrush current, which otherwise might destroy the devices. This paper presents the operating principles, analysis, and simulation results, and compares them to the conventional switched-inductor Z-source inverter. In order to verify the performance of the proposed converters, a laboratory prototype was constructed with 60 Vdc input to test both configurations.

Globally Stable Adaptive Fuzzy Control for Strict-feedback Nonlinear Systems

A new adaptive fuzzy controller for uncertain strict-feedback nonlinear systems is proposed. All the previous approximator-based adaptive control algorithms for the strict-feedback nonlinear systems are based on backstepping scheme and guarantee semi-global closed-loop system stability. This paper proposes a new globally stabilizing adaptive fuzzy controller for strict-feedback nonlinear system without backstepping. To this end, an online self-structuring adaptive fuzzy system is employed. The proposed adaptive fuzzy controller is considerably simpler than the previous ones based on backstepping. Only one FLS is employed to approximate a lumped uncertain nonlinearity, which highlights the simplicity of our proposed control scheme.

New approach for cascaded-transformers-based multilevel inverter with an efficient switching function

A new multilevel PWM inverter is presented to improve the system characteristic of a prior 11-level shaped PWM inverter scheme. In appearance, it consists of three full-bridge modules and three cascaded transformers; therefore, the configuration of the proposed multilevel PWM inverter is equal to that of the prior one. Only the turn-ratio of a transformer and its corresponding switching function are different from each other. Based on these differences, the proposed multilevel PWM inverter has two promising advantages. First, output voltage levels increase almost two fold. Consequently, it can generate more sinusoidal output voltage waves. Second, due to a suitable switching pattern, it lightens power imposed on the transformer, which is used for compensating output voltages with chopped pulses between steps. Operational principle of the proposed 19-level shaped PWM inverter is analysed with comparisons of the prior 11-level shaped PWM inverter. The validity of the proposed inverter system is verified by computer-aided simulations and experimental results based on a 1kW prototype.

Visual control of an autonomous vehicle using neural networks

This paper describes a control scheme for on autonomous vehicle with visual sensors, which uses visual information to guide itself along roadways. The control system integrates visual data into the servo process directly, instead of subdividing the process by reconstructing three-dimensional shape from two-dimensional image data, and relying on geometric reasoning for a vehicle-centered representation of the road. An artificial neural network system is used for determining the steering angle required to move the vanishing point and vanishing line of the road to the desired position in the camera image. The validity and the effectiveness of the proposed control scheme are verified by a computer simulation of the autonomous vehicles performance.

A Study on Design of 50kW PMSG for Micro-grid Application

In this paper, the 50kW aerogenerator which is applicable to the microgrid was designed and analyzed by using commercial simulation program Maxwell 2D. Particularly, the suggested PMSG to reduce the cogging torque introduced the offset and skew concept. The suggested optimal value of offset and skew was decided by 2mm and 60 degree of electric angle. The simulation results of the PMSG when load operation condition showed the average harmonic distortion 1.3%, voltage 322.41V, current 94.95A, and iron loss 9.73W, eddy current loss 73.68W, copper loss 3.52kW. The capacity of aerogenerator calculated 61.56kW, and the suggested design process can be applied to higher capacity generator.

Psim and Matlab simulations analysis on 3-Phase Z-Source inverter

There are lots of simulation methods can be used in electronic circuit analysis such as Psim, Matlab and Pspice etc. Here the analyses about 3-Phase Z-Source inverter are done to find the characteristics when different control method is applied. There are lots of control methods can be used in the 3- phase Z-Source inverter. In this paper several typical control methods are analyzed and compared through the simulation in the PSIM and Matlab.

A study on the HBML inverter using the cascaded transformers

In this paper, an efficient switching pattern to equalize the size of transformer is proposed for a multi-level inverter using cascaded transformers. It bases on the prior selected harmonic elimination PWM (SHEPWM) method. Because the maximum magnetic flux imposed on each transformer becomes exactly equal each other, all transformers can be designed with the same size regardless of their position. Therefore, identical full-bridge inverter units can be utilized, the modularity can be more efficient and the manufacture can be easier