This paper addresses the analysis and design of fuzzy control systems for a class of complex uncertain single-input single-output nonlinear systems. The proposed method represents the nonlinear system using a Takagi-Cugeno fuzzy model and construct a global fuzzy logic controller by blending all local state feedback controllers with a sliding mode controller. Unlike the commonly used parallel distributed compensation technique, we can design a global stable fuzzy controller without finding a common Lyapunov function for all local control systems, and can obtain good tracking performance by using sliding mode control theory. Furthermore, stability analysis is carried out not for the fuzzy model but for the real nonlinear system with uncertainties. Duffing forced oscillation sysmte is used as an example to show the effectiveness and feasibility of the proposed method.

This paper presents a new algorithm for hierarchical optimal control of nonlinear systems. The proposed method is simple because the solutions are obtained by only exchanging informations of coefficient vector based on interaction prediction principle and FWT(fast Walsh transform) in upper and lower level. Since we solve two point boundary problem with Picard's iterative method and the backward integral operational matrix of Walsh function to obtain the optimal vector of each independent subsystem, the algorithm is simple and its operation is fast without inverse matrix and kronecker product operation. In simulation, the proposed algorithm's usefulness is proved by comparison with the global optimal control methods.

This paper presents a systematic approach to the input-output data-based fuzzy modeling for the complex and uncertain nonlinear systems, in which the conventional mathematical models may fail to give the satisfying results. To do this, we propose a new method that can yield a successful fuzzy model using a mGA hybrid schemes with a fine-tuning method. We also propose a new coding method fo chromosome for applying the mGA to the structure and parameter identifications of fuzzy model simultaneously. During mGA search, multi-purpose fitness function with a penalty process is proposed and adapted to guarantee the accurate and valid fuzzy modes. This coding scheme can effectively represent the zero-order Takagi-Sugeno fuzzy model. The proposed mGA hybrid schemes can coarsely optimize the structure and the parameters of the fuzzy inference system, and then fine tune the identified fuzzy model by using the gradient descent method. In order to demonstrate the superiority and efficiency of the proposed scheme, we finally show its applications to two nonlinear systems.

It is difficult to analyze the charging characteristics of the lead-acid battery, because of the influences by various non-linear and time-variant parameters. In this study, the charging characteristics of high capacity industrial lead-acid battery 630 Ah was investigated through experiments with respect to the variations of temperature and the aged state of battery during the charging process. The database of those characteristics is established from the results of experiments, and the fuzzy logic charging algorithm is suggested using them. The results of experiment shows that the industrial lead-acid batteries can be always fully charged within the saved charging time by the proposed charging control algorithm adapting to the variations of charging condition. This new charging concept will be useful for developing the advanced battery charger improving the efficiency of storing electricity.

Active noise control is an approach to noise reduction in which a secondary noise source that destructively interferes with the unwanted noise. In general, active noise control systems rely on multiple sensors to measure the unwanted noise field and the effect of the cancellation. This paper develops an approach that utilizes a single sensor. The noise field is modeled as a stochastic process, and a time-adaptive algorithm is used to adaptively estimate the parameters of the process. Based on these parameter estimates, a canceling signal is generated. Opppenheim model assumed that transfer function characteristics from the canceling source to the error sensor is only propagation delay. But this paper proposes a modified Oppenheim model by considering transfer characteristics of acoustic device and noise path. This transfer characteristics is adaptively cancelled by adaptive model. This is proved by computer simulation with artifically generated random noise and sine wave noise. The details of the proposed architecture, and theoretical simulation and experimental results of the noise cancellation system for three dimension enclosure are presented in the paper.

The precise speed and position control technique for Brushless DC Motor demands accurate position and speed feedback information. Generally, resolver or absolute encoders are used as speed and positiion sensor. But they increase cost and more problem happens at low speed than high speed specially. Therefore, in this paper, optimal speed observer is proposed for decreasing size and cost of whole system. And also, we consider the error problem about the system modeling and measurement at low speed range as well as high speed. The overall system consists of two parts, a drive and a speed observer. We make use of Least square curve fitting algorithm as speed observer and can overcome low resolution by proposed observer. Also, because of using the signal of hall sensor, robust control is possible in low speed as well as high speed for the change of the parameters of the system and disturbance. To construct observer using the signal of hall sensor, we design the pulse multiplier circuit and the software of microprocessor, AT89CC2051. Finally, the performance of the proposed observer is exemplified by some simulations and experiments.

In this paper, we propose an attitude controller for an unstructured object using CMG(Control Moment of Gyro) subsystem, which has a stabilizer function. The CMG subsystem consists of one motor for spinning the wheel and the other motor for turning the outer gimbal. While the wheel of CMG subsystem is spinning at high speed, applying force to the spin axis of the wheel leads the torque about the vertical axis. We utilize the torque to control the attitude of object in this study. For the stabilizer function, in additiion, holding the load at the current position, the power applied to the gimbal motor of CMG will be cut, which result in the braking force to stop the load by gyro effect. However, due to the gear reduction connected to outer gimbal, slow load motion cannot generate the braking force. Thus, in this study, we are willing to make a holding force by applying control power to the gimbal motor from the signal of piezoelectric gyroscopic sensor that detected the angular velocity of the load. These two features are demonstrated in experiment, carrying a beam with crane. As a result, load was started to rotate by controlling gimbal positiion and was stopped by turning off the gimbal power. Moreover, slow movement of the load was also rejected by additional control with gyroscopic sensor.

A three-level decoupled sliding mode controller is developed to achieve asymptotic stability for a class of sixth-order nonlinear systems. The sixth-order system is decoupled into three subsystems according to the structure of the whole system. Each subsystem has a separate control target in the form of a sliding surface. The information of the third sliding surface is transferred to the second one through an intermediate variable and the information of the second sliding surface is transferred to the first one through another intermediate variable. Consequently, the controller designed on the basis of the first sliding surface can make three subsystems move toward their sliding surfaces, respectively. The three-level decoupled sliding mode controller is applied to the double-inverted pendulum problem where the zero stable states are required.

A fuzzy PID controller is proposed for the posture control of a two DOF robot vehicle inspecting the defects of the inner wall of sewage pipes. The main difficulty in controlling these kinds of vehicles lies in that the center of two mobile shafts does not coincide with the weight center of the vehicle due to its long and wide shape. In this case the previous controller, based on the assumption that the gap between these centers are small, can not guarantee satisfactory transient response characteristics. In this paper, this gap is included in the mathematical modelling of the robot kinematics, and in order to compensate the unsatisfactory transient response characteristics, the fuzzy PID controller is proposed. This controller tunes the PID control gains with respect to the current state of the errors between the reference and the current postures. A series of simulations has been performed to investigate the tracking performance of the proposed controller for the lane changing path and the robustness to the external disturbance. The simulation results show that the proposed controller has a satisfactory tracking performance in the transient state as compared with that of the backstepping control given in reference.

This paper analyzes interference power, Erlang capacity, the number of handoff occurrences, and call blocking probability with respect to the cell radius, the soft handoff region, and the mobile's velocity in a CDMA hierarchical cellular system. The microcell cellular system has the higher Erlang capacity than the macrocell cellular system. However, the microcell cellular system, which has a high system capacity through frequency reuse has the call blocking probability higher than macrocell cellular system. Also the interference power and the call blocking probability are decreased with the operation of soft handoff. Therefore, this paper presents the optimization of soft handoff region so as to maximize system's Erlang capacity with the low the call blocking probability according to mobile's velocity in the CDMA hierarchial cellular system.

A scheme is proposed for measuring similarities between the binary pulse signals in the pulse-code modulation using the Integra-Normalizer. The Integra-Normalizer provides a better interpretation of the relationship between the pulse signals by removing redundant codes, which maps all possible observed signals to one of the codes to be received with relative similarities between each pair of compared signals. The proposed method provides better error tolerance than L2 metric, such as Hamming distance, since the distances between pulse signals are measured not useful for the time-delay detection in the pulse-code modulation.