Catálogo de publicaciones - libros

The paper proposes a method to control the motion orbit of a cartoon object based on chaos theory. We first propose an adaptive delaying feedback controlling method which can control the Lorenz system to generate periodic, quasi-periodic and chaotic orbits. Then we apply our method to the topic of cartoon object motion controlling. It can enrich the motion type of the object thus enhances the visual effect of the cartoon video. The experiments validate the controlling results of the proposed method. Our research leads to a new area in which the chaotic theory is applied in the field of multimedia processing.

In human society, learning is essential to intelligent behavior. However, people do not need to learn everything from scratch by their own discovery. Instead, they exchange information and knowledge with one another and learn from their peers and teachers. When a task is too complex for an individual to handle, one may cooperate with its partners in order to accomplish it. Like human society, cooperation exists in the other species, such as ants that are known to communicate about the locations of food and move it cooperatively. Using the experience and knowledge of other agents, a learning agent may learn faster, make fewer mistakes, and create rules for unstructured situations. In the proposed learning algorithm, an agent adapts to comply with its peers by learning carefully when it obtains a positive reinforcement feedback signal, but should learn more aggressively if a negative reward follows the action just taken. These two properties are applied to develop the proposed cooperative learning method conceptually. The algorithm is implemented in some cooperative tasks and demonstrates that agents can learn to accomplish a task together efficiently through a repetitive trials.

In this paper, the application of fuzzy set theory, genetic algorithms and rough set theory techniques to the control of the High Voltage Direct Current (HVDC) system is studied. A fuzzy adaptive control scheme with the aid of rough set theory via genetic algorithms (GAs) finding the center scaling-factors in place of the classical control is proposed. On the one hand, genetic algorithm gets optimal parameters of an accurate domain model, which tunes the scaling factors of fuzzy adaptive control but is hardly established in a non-liner system. On the other hand, fuzzy adaptive control deals with the dynamics and complexity of responses from a HVDC system in the operation points, by adjusting its control parameters with the aid of rough tuner adaptively. Our study includes a brief introduction to fuzzy sets, fuzzy control and rough set algorithms, both theory and application. We also evaluate the performance of fuzzy adaptive control by simulation in the paper. The focus of our experiments is on the constant current control in HVDC system. The result shows there are many improvements offered by the fuzzy control scheme based on rough set theory in comparison with the conventional HVDC control scheme.

An adaptive fuzzy integral type sliding mode control method is proposed in this paper to compensate nonlinear dynamic friction that exists in single-axle motion control system and to improve the system position tracking performance. A kind of integral type sliding mode function is introduced, and the sliding mode control law that is obtained by using this sliding function does not include the switch controller that exists in conventional variable structure control law, therefore, the chattering phenomenon can be avoided. The parameter adaptive laws are derived in the sense of Lyapunov stability theorem, the parameters in adaptive laws are optimized by genetic algorithm. Simulation results show that adaptive fuzzy integral type sliding mode controller can achieve favorable tracking performance and robust with system nonlinear dynamic friction.

Conventional hysteresis control schemes for direct torque control (DTC) of dual-three-phase induction machine (DTPIM) usually result highly distorted current waveforms. In this paper, fuzzy space voltage modulation technique is presented for DTPIM. Using two fuzzy controllers, amplitude and space angle of desired stator voltage vector, are obtained dynamically. Combined with unified pulse width modulation method, direct torque control is applied to DTPIM. Simulation results show that fast dynamic responses are achieved. The ripple of torque and the harmonics of stator current in steady state can be reduced remarkably compared with conventional DTC method.

In this paper, a suitable particle swarm optimization (PSO) is firstly proposed to obtain the pulse width modulation (PWM) switching time which maintaining a required fundamental voltage and a minimal total harmonic distortion (THD) for very high power medium voltage induction motor drives fed by a double three-level inverter (DTI). The simulation results show that double three-level inverter based variable frequency drive system needs switches with lower voltage rating, and performs lower voltage harmonics than one single three-level inverter. After optimizing the PWM switching time by using particle swarm optimization, the motor drive voltage quality improves more.

This paper studies the application of the adaptive fuzzy sliding mode control (AFSMC) strategies for reducing the dynamic responses of the bridges with sliding bearing isolation hybrid protective system. Hence it is necessary to develop non-linear control methods. AFSMC is a combination of the sliding mode control (SMC) and the Fuzzy control. The performance and robustness of the proposed control methods are all demonstrated by numerical simulation. Simulation results demonstrate that the presented methods are viable and an attractive control strategy for application to seismically excited bridges with sliding bearing isolation.

The are various definitions of instantaneous frequency (IF) but most of them have short comings. The most popular of these definitions, is the one given by Cohen. To estimate IF accuratly, techniques become more and more complex. This paper introduces the idea of aggregate spectrogram (AS). When we are not interested in the entire spectrum (e.g., finding IF), it is better to find out AS which gives an aggregate view of the spectrogram rather than calculating the individual frequencies. Some properties of AS are also defined. The AS lowers the computational complexity. This paper also presents a technique to construct an AS and finding the IF from the AS.

The orthogonal function neural network is utilized to realize the general synchronization of chaotic systems with different structures. The driving system and the reference system are both disturbed by the external perturbation. Continuous controller is utilized to realize the general synchronization of chaotic systems according to nonlinear control theory. Lorenz system and Rssler system are utilized to simulate to illustrate the performance of the proposed method. The simulation results can show the validity of the proposed method.

In this paper, an image-based robust controller for tracking control of robot manipulators using a single camera is proposed. The proposed controller has robustness to parametric uncertainties of the robot manipulator and compensation for uncertainties included in the image Jacobian. The stability of the closed-loop system is proved by Lyapunov approach. The performance of the proposed method is demonstrated by experiments on a 5-link robot manipulator with two degree of freedom.