Chen Chien Hsu

Robust adaptive fuzzy-neural control of nonlinear dynamical systems using generalized projection update law and variable structure controller

In this paper, a robust adaptive fuzzy-neural control scheme for nonlinear dynamical systems is proposed to attenuate the effects caused by unmodeled dynamics, disturbance, and modeling errors. A generalized projection update law, which generalizes the projection algorithm modification and the switching-sigma adaptive law, is used to tune the adjustable parameters for preventing parameter drift and confining states of the system to the specified regions. Moreover, a variable structure control method is incorporated into the control law so that the derived controller is robust with respect to unmodeled dynamics, disturbances, and modeling errors. To demonstrate the effectiveness of the proposed method, several examples are illustrated in this paper.

Distance measurement based on pixel variation of CCD images

This paper presents a distance measurement method based on pixel number variation of CCD images by referencing to two arbitrarily designated points in the image frames. By establishing a relationship between the displacement of the camera movement along the photographing direction and the difference in pixel count between reference points in the images, the distance from an object can be calculated via the proposed method. To integrate the measuring functions into digital cameras, a circuit design implementing the proposed measuring system in selecting reference points, measuring distance, and displaying measurement results on CCD panel of the digital camera is proposed in this paper. In comparison to pattern recognition or image analysis methods, the proposed measuring approach is simple and straightforward for practical implementation into digital cameras. To validate the performance of the proposed method, measurement results using the proposed method and ultrasonic rangefinders are also presented in this paper.

Design of Infrared Electronic-Toll-Collection Systems With Extended Communication Areas and Performance of Data Transmission

Based on our previous works in the design of an infrared emitter for electronic-toll-collection (ETC) applications, we use the unidirectional cosinen functions to approximate the irregular radiation pattern for typical infrared low-cost commercial light-emitting diodes (LEDs) with a half-intensity angle Φ1/2 = 10°. With the aid of this approximation, the main characteristics of the performance of an infrared ETC system utilizing this type of LED as the emitter can be investigated based on the received signal strength of the system. For on-off keying, a simple model connecting the received signal strength and the bit error rate (BER) of the system is further established. From the calculated or the measured received signal strength of the system, it is not difficult to estimate the system performance in terms of the BER by this simple model. Roughly speaking, for a typical setting of the circuit parameters and a typical uplink and downlink data-transmission protocol, the data transmission can be very successful in terms of a very low BER if the received signal strength is 1.3 times stronger than the signal strength received at the communication boundary. The emitter presented in this paper is able to produce a relatively extended communication area in the vehicle-traveling direction, resulting in longer communication time interval for the data transmission between the onboard unit (OBU) and the roadside unit (RSU) than conventional emitters. Furthermore, the design presented in this paper is validated by experimental measurement to demonstrate its effectiveness.

Design of optimal controller for interval plant from signal energy point of view via evolutionary approaches

Design of an optimal controller minimizing the integral of squared error (ISE) of the closed-loop system for an interval plant via evolutionary approaches is proposed in this paper. Based on a worst-case design philosophy, the design problem is formulated as a minimax optimization problem from the signal energy point of view, and subsequently solved by two interactive genetic algorithms. To ensure robust stability of the closed-loop system, root locations of the Kharitonov polynomials associated with the characteristic polynomial are used to establish a constraint handling mechanism for incorporation into the fitness function to effectively evaluate chromosomes in the current population. To accelerate the derivation process to obtain the optimal controller, alternative approaches based on the two-phase evolutionary scheme are also proposed, in which the worst-case ISE is suitably estimated via information provided by the Kharitonov plants. Thus, the derived controller not only stabilizes the interval plant, but also minimizes the ISE criterion of the closed-loop system. Constraints on higher order plants and controller order commonly encountered by conventional design methods are therefore removed by using the proposed approach.

Hardware/software co-design of particle filter and its application in object tracking

This paper presents a hardware/software co-design method for particle filter based on System On Program Chip (SOPC) technique. Considering both the execution speed and design flexibility, we use a NIOS II processor to calculate weight for each particle and a hardware accelerator to update particles. As a result, execution efficiency of the proposed hardware/software co-design method of particle filter is significantly improved while maintaining design flexibility for various applications. To demonstrate the performance of the proposed approach, a real-time object tracking system is established and presented in this paper. Experimental results have demonstrated the proposed method have satisfactory results in real-time tracking of objects in video sequences.

Minimum-phase criterion on sampling time for sampled-data interval systems using genetic algorithms

In this paper, a genetic algorithm-based approach is proposed to determine a desired sampling-time range which guarantees minimum phase behaviour for the sampled-data system of an interval plant preceded by a zero-order hold (ZOH). Based on a worst-case analysis, the identification problem of the sampling-time range is first formulated as an optimization problem, which is subsequently solved under a GA-based framework incorporating two genetic algorithms. The first genetic algorithm searches both the uncertain plant parameters and sampling time to dynamically reduce the search range for locating the desired sampling-time boundaries based on verification results from the second genetic algorithm. As a result, the desired sampling-time range ensuring minimum phase behaviour of the sampled-data interval system can be evolutionarily obtained. Because of the time-consuming process that genetic algorithms generally exhibit, particularly the problem nature which requires undertaking a large number of evolution cycles, parallel computation for the proposed genetic algorithm is therefore proposed to accelerate the derivation process. Illustrated examples in this paper have demonstrated that the proposed GA-based approach is capable of accurately locating the boundaries of the desired sampling-time range.

Digital redesign of uncertain interval systems based on time-response resemblance via particle swarm optimization

In this paper, a novel design approach based on time-response resemblance of the closed-loop system via particle swarm optimization is proposed to improve performance of the redesigned digital system for continuous-time uncertain interval systems. The design rationale of the proposed approach is to derive a digital controller for the redesigned digital system so that step response sequences corresponding to the extremal sequence energy closely match those of their continuous counterpart under the perturbation of the plant parameters. By suitably formulating the design problem as an optimization problem, an evolution framework incorporating three PSOs (particle swarm optimizations) is presented to derive a set of optimal parameters for the digital controller. Computer simulations have shown that time responses of the redesigned digital system having an interval plant have a better resemblance to their continuous-time counter part in comparison those obtained using existing open-loop discretization methods.

Particle swarm optimization incorporating simplex search and center particle for global optimization

This paper proposes a hybrid approach incorporating an enhanced Nelder-Mead simplex search scheme into a particle swarm optimization (PSO) with the use of a center particle in a swarm for effectively solving multi-dimensional optimization problems. Because of the strength of PSO in performing exploration search and NM simplex search in exploitation search, in addition to the help of a center particle residing closest to the optimum during the optimization process, both convergence rate and accuracy of the proposed optimization algorithm can be significantly improved. To show the effectiveness of the proposed approach, 18 benchmark functions will be adopted for optimization via the proposed approach in comparison to existing methods.

Genetic algorithm-derived digital integrators and their applications in discretization of continuous systems

A set of enhanced digital integrators (EDI) with improved accuracy using genetic algorithms are proposed in this paper. By specifying a desired power for the integrator to be sought and the interval for comparison, chromosomes consisting of parameters of the enhanced digital integrator are then searched by the genetic algorithm based on root mean squared (RMS) error between the original integrator and candidates of the enhanced digital integrator. Thus, all the best parameters of an optimal enhanced digital integrator can be evolutionarily obtained. To demonstrate the effectiveness of the proposed approach, the derived enhanced digital integrators are used to obtain the discrete approximation for continuous systems.

Image-Based System for Measuring Objects on an Oblique Plane and Its Applications in 2-D Localization

This paper presents an image-based framework for measuring target objects on an oblique plane by using a single charge-coupled device camera and two laser projectors mounted in parallel beside the camera. Because of the alignment of the laser beams, which form in parallel with the optical axis of the camera, laser-projected spots in the image can be processed to establish relationships between distance and pixel counts of the projected spots in the image. Based on simple geometrical derivations without complex image processing, the proposed approach can successfully measure the photographic distance, the distance between two arbitrary points on the oblique surface, and the incline angle of the oblique surface. Thanks to its ranging capability, the proposed image-based measuring system is further applied to localize objects on a ground surface in addition to depth measurement. To demonstrate the feasibility of the proposed approach for practical applications, we propose a surveillance framework under which a pan-tilt-zoom camera tracks objects in an environment according to the 2-D localization results obtained via the proposed method. Experimental results have demonstrated the effectiveness of the proposed approach in distance measurement, as well as localization of objects on an oblique plane.