Wen-Jye Shyr

Teaching mechatronics: An innovative group project-based approach

This study presents an innovative group project‐based approach to teaching mechatronics. Mechatronics is a complex, highly technical and multidisciplinary field involving the design and manufacture of integrated products. Mechatronics course at the undergraduate level is rapidly increasing across the world. Most courses require student teams to design a product. The complexity of student projects can make administration of mechatronics courses extremely difficult. Students develop both practical and theoretical understanding of mechatronics while working on group projects. They also develop the interpersonal and communication skills needed to work in a multi‐disciplinary field. This study describes a group project‐based approach for enabling teams of students to complete mechatronics projects. A set of heuristic guidelines is also proposed. At the National Changhua University of Education in the Department of Industrial Education and Technology, this approach has yielded high student satisfaction and achievement.

Adaptive Pattern Nulling Design of Linear Array Antenna by Phase-Only Perturbations Using Memetic Algorithms

In this paper, the pattern nulling of a linear array for interference cancellation is derived by phase-only perturbations using memetic algorithm. It is proposed to improve the search ability of genetic algorithms. Memetic algorithm is a kind of an improved type of the traditional genetic algorithm. By using local search procedure, it can avoid the shortcoming of the traditional genetic algorithm, whose termination criteria are set up by using the trial and error method. The memetic algorithm is applied to find the pattern nulling of the proposed adaptive antenna. This design for radiation pattern nulling of an adaptive antenna can suppress interference by placing nulls at the directions of the interfering sources, i.e., to increase the signal to interference ratio (SIR). This proposed method is that an innovative adaptive antenna optimization technique is also able to solve the multipath problem which exists in practical wireless communication systems. The example is provided to justify the proposed phase-only perturbations approach based on memetic algorithms. Computer simulation results are given to demonstrate the effectiveness of the proposed method

Integrating Laboratory Activity Into a Junior High School Classroom

This paper presents a wind power system laboratory activity and an outline for evaluating student performance in this activity. The work described here was to design and implement the laboratory to assist teachers in achieving the teaching objective of this activity. The laboratory teaching activities introduce energy sources, wind energy technology, electricity storage, and wind power system testing. The wind power system testing activity includes eight topics: setting up the experimental module, operating instruments, wind velocity measurement, rotor diameter activity, wind speed activity, blade angle activity, blade number activity, and data summary. These laboratory activities were first introduced in a Taiwanese junior high school in 2007. This laboratory activity effectively introduced students to wind energy technology through activity participation. The objective of this activity is for the students to gain not only an understanding of the concept of wind power electricity generation, but a greater confidence in investigating, questioning, and experimenting with renewable energy ideas. The students are able to relate the experiments to electronic and computer engineering.

Optimizing Beam Pattern of Linear Adaptive Phase Array Antenna Based on Particle Swarm Optimization

In this paper, an innovative optimal radiation pattern of an adaptive linear array is derived by phase-only perturbations using a Particle Swarm Optimization (PSO) algorithm. An antenna array is often made as an adaptive antenna. An optimal radiation pattern design for an adaptive antenna system is not only to suppress interference by placing a null in the direction of the interfering source but also to derive the maximum power pattern in the direction of the desired signal. The Signal Interference Ratio (SIR) can be maximized. The PSO algorithm is a new methodology in this study area, which can handle adaptive radiation pattern of antenna array. In this paper, an optimal radiation pattern of linear array is derived by phase-only perturbations using a PSO algorithm. PSO algorithms will be stated and computed for this problem. Then, the optimal solution can be derived, and simulation results are also presented in this paper.

Another sufficient condition for the stability of grey discrete-time systems

Abstract In this paper, the stability of grey discrete-time systems is discussed whose state matrices are interval matrices. A new approach is obtained which guarantee the stability of grey discrete-time systems. The sufficient condition for robust stability of grey time delay systems subjected to interval systems is also derived. By mathematical analysis, the stability criterion is less conservative than those in previous results. Examples are given to compare the proposed method with reported recently.

Optimal design using clonal selection algorithm

In this paper, the Clonal Selection Algorithm (CSA) is employed by the natural immune system to define the basic features of an immune response to an antigenic stimulus. This paper synthesizes the advantages of clonal selection algorithm and proposed optimal design problem using clonal selection algorithm which is a basis of the immune system. CSA, the essence of immune algorithm, is effective to solve optimal problem. The clonal selection algorithm is highly parallel and presents a fine tractability in terms of computational cost. Like the genetic algorithm, clonal selection algorithm is a tool for optimum solution. Clonal selection algorithm and genetic algorithm are used to reach the optimization performances for two numerical function. Then those results are compared each other. These proposed algorithms are shown to be an evolutionary strategy capable of solving optimal design problem.

Development of Remote Monitoring and a Control System Based on PLC and WebAccess for Learning Mechatronics

This study develops a novel method for learning mechatronics using remote monitoring and control, based on a programmable logic controller (PLC) and WebAccess. A mechatronics module, a Web-CAM and a PLC were integrated with WebAccess software to organize a remote laboratory. The proposed system enables users to access the Internet for remote monitoring and control of the mechatronics module via a web browser, thereby enhancing work flexibility by enabling personnel to control mechatronics equipment from a remote location. Mechatronics control and long-distance monitoring were realized by establishing communication between the PLC and WebAccess. Analytical results indicate that the proposed system is feasible. The suitability of this system is demonstrated in the department of industrial education and technology at National Changhua University of Education, Taiwan. Preliminary evaluation of the system was encouraging and has shown that it has achieved success in helping students understand concepts and master remote monitoring and control techniques.

Introduction and Comparison of Three Evolutionary-Based Intelligent Algorithms for Optimal Design

Engineering design studies can often be cast in terms of optimization problems. However, for such an approach to be worthwhile, designers must be content that the optimization approaches employed is fast convergence. Usefulness of heuristic algorithm as the search method for diverse optimization problems is examined. Evolutionary algorithms (EAs) are stochastic search methods that mimic the natural biological evolution and/or the social behavior of species. Such algorithms have been developed to arrive at near-optimum solutions to large-scale optimization problems, for which traditional mathematical techniques may fail. This paper compares the formulation and results of three evolutionary-based algorithms: genetic algorithm, clonal selection algorithm and particle swarm optimization. A brief description of each algorithm is presented. Benchmark comparisons among these algorithms are presented optimization problems, in terms of processing time, convergence speed, and quality of the results. The simulation results show that compared with genetic algorithm and clonal selection algorithm, the proposed particle swarm optimization based algorithm can improve the quality of the solution while speeding up the convergence process. Three words can summarize the main features of the proposed approach: faster, cheaper, and simpler.

The hybrid genetic algorithm for blind signal separation

In this paper, a hybrid genetic algorithm for blind signal separation that extracts the individual unknown independent source signals out of given linear signal mixture is presented. The proposed method combines a genetic algorithm with local search and is called the hybrid genetic algorithm. The implemented separation method is based on evolutionary minimization of the separated signal cross-correlation. The convergence behaviour of the network is demonstrated by presenting experimental separating signal results. A computer simulation example is given to demonstrate the effectiveness of the proposed method. The hybrid genetic algorithm blind signal separation performance is better than the genetic algorithm at directly minimizing the Kullback-Leibler divergence. Eventually, it is hopeful that this optimization approach can be helpful for blind signal separation engineers as a simple, useful and reasonable alternative.

Development of working competence items for mechatronics with graphical monitoring and control

The purpose of this study was to identify the working competence items which considered important for mechatronics with graphical monitoring and control for industry requirements. The data were collected by document analysis, expert interview, and Delphi technique surveys. The Delphi technique involved three questionnaire surveys of field experts and scholars followed by Kendall coefficient of concordance analysis to evaluate the Chi‐Square value and examine the consistency of respondent opinions to check the items whether reach the level of significance. Further, a Kolmogorov–Smirnov one‐sample test examined working competence items using 31 items divided into 7 domains. The survey items were selected according to consensus opinions of 10 experts by Delphi survey technique. The findings of this study provide guidelines for assessing professional working competence for mechatronics by applying graphical monitoring and control systems. The research findings reveal the practical competency requirements for students in a technology institute program, and a relevant curriculum is suggested.