Heng-Ming Tai

Autonomous local path planning for a mobile robot using a genetic algorithm

This work presents results of our work in development of a genetic algorithm based path-planning algorithm for local obstacle avoidance (local feasible path) of a mobile robot in a given search space. The method tries to find not only a valid path but also an optimal one. The objectives are to minimize the length of the path and the number of turns. The proposed path-planning method allows a free movement of the robot in any direction so that the path-planner can handle complicated search spaces.

DC Link Active Power Filter for Three-Phase Diode Rectifier

In this paper, a dc link active power filter (APF) for three-phase diode rectifier is proposed. The proposed dc link APF, which is composed of two series-connected bidirectional boost converters, intends to eliminate the input current harmonics. It is paralleled at the dc link of the diode rectifier and is coupled to the ac input with three line-frequency switches. Compared with the full power processed power factor correction (PFC) solution, the dc link APF is partially power processed in that it only compensates for the harmonic current component at the dc link. Thus, it features with lower power processing. Moreover, it exhibits better total harmonic distortion of the ac line current when compared with the traditional ac side shunt APF. Voltage and current loop models are developed for average current control, and the selection of the current loop bandwidth is presented. Switching stresses of the ac APF, the dc link APF, and the six-switch PFC are also calculated and analyzed. Experimental and simulation results demonstrate the effectiveness of this dc link APF.

Double-Frequency Buck Converter

Improving the efficiency and dynamics of power converters is a concerned tradeoff in power electronics. The increase of switching frequency can improve the dynamics of power converters, but the efficiency may be degraded. A double-frequency (DF) buck converter is proposed to address this concern. This converter is comprised of two buck cells: one works at high frequency, and another works at low frequency. It operates in a way that current in the high-frequency switch is diverted through the low-frequency switch. Thus, the converter can operate at very high frequency without adding extra control circuits. Moreover, the switching loss of the converter remains small. The proposed converter exhibits improved steady state and transient responses with low switching loss. An ac small-signal model of the DF buck converter is also given to show that the dynamics of output voltage depends only on the high-frequency buck cell parameters, and is independent of the low-frequency buck cell parameters. Simulation and experimental results demonstrate that the proposed converter greatly improves the efficiency and exhibits nearly the same dynamics as the conventional high-frequency buck converter. Furthermore, the proposed topology can be extended to other dc-dc converters by the DF switch-inductor three-terminal network structure.

A neural network-based tracking control system

An application of the backpropagation neural network to the tracking control of industrial drive systems is presented. The merits of the approach lie in the simplicity of the scheme and its practicality for real-time control. Feedback error trajectories, rather than desired and/or actual trajectories, are employed as inputs to the neural network tracking controller. It can follow any arbitrarily prescribed trajectory even when the desired trajectory is changed to that not used in the training. Simulation was performed to demonstrate the feasibility and effectiveness of the proposed scheme. >

A wavelet-based fragile watermarking scheme for secure image authentication

This paper proposes a wavelet-based fragile watermarking scheme for secure image authentication. In the proposed scheme, the embedded watermark is generated using the discrete wavelet transform (DWT), and then the improved security watermark by scrambling encryption is embedded into the least significant bit (LSB) of the host image. The proposed algorithm not only possesses excellent tamper localization properties and greater security against many attacks, but also demonstrates a new useful feature that can indicate whether the modification made to the image is on the contents or the embedded watermark. If only the watermark is modified, the authenticity of the image is assured, instead of being declared as a counterfeit. Experimental results illustrate the effectiveness of our method.

A new watermarking method based on chaotic maps

This paper presents a new digital watermarking method based on chaotic maps. Different from most of the existing chaotic watermarking methods, two chaotic maps are incorporated into the watermarking system to resolve the finite word length effect and to improve the systems resistance to attacks. One map is used for watermark generation, another as the private key. Simulation results show that the proposed digital watermarking system is feasible and robust to common signal processing procedures. In addition, it performs better than existing watermarking schemes and exhibits better protection than watermarking systems using only one chaotic map

Performance Analysis of a Block-Neighborhood-Based Self-Recovery Fragile Watermarking Scheme

In this paper, we present the performance analysis of a self-recovery fragile watermarking scheme using block-neighbor- hood tamper characterization. This method uses a pseudorandom sequence to generate the nonlinear block-mapping and employs an optimized neighborhood characterization method to detect the tampering. Performance of the proposed method and its resistance to malicious attacks are analyzed. We also investigate three optimization strategies that will further improve the quality of tamper localization and recovery. Simulation results demonstrate that the proposed method allows image recovery with an acceptable visual quality (peak signal-to-noise ratio (PSNR) as 25 dB) up to 60% tampering.

2-D direction-of-arrival estimation of coherent signals using cross-correlation matrix

In this paper, we present a new two-dimensional (2-D) direction-of-arrival (DOA) angle estimation method for coherent or highly correlated narrowband signals using L-shape arrays. The proposed method decorrelates the coherent incident signals and reconstructs the signal subspace using the cross-correlation matrix. Then the shift invariance property of the array geometry is employed to estimate the azimuth and elevation angles. This approach enables the 2-D DOA estimation without the use of peak search and is robust to noise. Moreover, we extend the proposed forward method to the forward/backward one. Experimental results demonstrate that satisfactory performances of the proposed methods are obtained for correlated signals in the low signal-to-noise ratio (SNR) situations and with small number of snapshots.

Cell mapping for controller design and evaluation

Cell mapping is a powerful computational technique for analyzing the global behaviour of nonlinear dynamical systems. It simplifies the task of analyzing a continuous phase space by partitioning it into a finite number of disjoint cells and approximating system trajectories as cell transitions. The resulting cell map provides global measures of stability and other performance characteristics that are valuable in system analysis and controller design. This article shows how cell mapping can be used to design high-performance, conventional and fuzzy, controllers. It also shows how cell maps can provide global performance measures of the designed controllers, including time optimality, controllability, and empirical assessments of robustness. Evaluating controller performance based on these global measures is superior to simply examining time domain responses for various initial conditions.

Incorporating cell map information in fuzzy controller design

Cell mapping is a powerful mechanism for evaluating the global behavior of nonlinear dynamical systems. A cell map conveys direct information about system dynamics, including the regions of stability, the set of controllable initial states and system trajectories. This paper shows how cell map information can be incorporated in a genetic algorithm for tuning fuzzy controller parameters. The resulting fuzzy controller exhibits superior performance to controllers designed using conventional techniques. It has near time-optimal characteristics with maximal stability and controllability.<<ETX>>