| 1 | A Novel Semiconductor CIGS Photovoltaic Material and Thin-Film ED Technology显示文摘In order to achieve low cost high efficiency thin film solar cells,a novel Semiconductor Photovoltaic (PV) active material CuIn 1-x Ga x Se 2 (CIGS) and thin film Electro Deposition (ED) technology is explored.Firstly,the PV materials and technologies is investigated,then the detailed experimental processes of CIGS/Mo/glass structure by using the novel ED technology and the results are reported.These results shows that high quality CIGS polycrystalline thin films can be obtained by the ED method,in which the polycrystalline CIGS is definitely identified by the (112),(204,220) characteristic peaks of the tetragonal structure,the continuous CIGS thin film layers with particle average size of about 2μm of length and around 1 6μm of thickness.The thickness and solar grade quality of CIGS thin films can be produced with good repeatability.Discussion and analysis on the ED technique,CIGS energy band and sodium (Na) impurity properties,were also performed.The alloy CIGS exhibits not only increasing band gap with increasing x ,but also a change in material properties that is relevant to the device operation.The beneficial impurity Na originating from the low cost soda lime glass substrate becomes one prerequisite for high quality CIGS films.These novel material and technology are very useful for low cost high efficiency thin film solar cells and other devices. | ZHENG Guang fu 1,YANG Hong xing 1,MAN Cheuk ho 1,WONG Wing lok 2, AN Da wei 1 and John BURNETT 1(1 Centre for Development of Solar Energy Technology,Department of Building Services Engineering, The Hong Kong Polytechnic University,Hong Kong,C | 2001 | Journal of Semiconductors2001，22，11： | 10 |
| 14 | Robust Iterative Learning Controller for the Non-zero Initial Error Problem on Robot Manipulator显示文摘Industrial robot system is a kind of dynamic system w ith strong nonlinear coupling and high position precision. A lot of control ways , such as nonlinear feedbackdecomposition motion and adaptive control and so o n, have been used to control this kind of system, but there are some deficiencie s in those methods: some need accurate and some need complicated operation and e tc. In recent years, in need of controlling the industrial robots, aiming at com pletely tracking the ideal input for the controlled subject with repetitive character, a new research area, ILC (iterative learning control), has been devel oped in the control technology and theory. The iterative learning control method can make the controlled subject operate as desired in a definite time span, merely making use of the prior control experie nce of the system and searching for the desired control signal according to the practical and desired output signal. The process of searching is equal to that o f learning, during which we only need to measure the output signal to amend the control signal, not like the adaptive control strategy, which on line assesses t he complex parameters of the system. Besides, since the iterative learning contr ol relies little on the prior message of the subject, it has been well used in a lot of areas, especially the dynamic systems with strong non-linear coupling a nd high repetitive position precision and the control system with batch producti on. Since robot manipulator has the above-mentioned character, ILC can be very well used in robot manipulator. In the ILC, since the operation always begins with a certain initial state, init ial condition has been required in almost all convergence verification. Therefor e, in designing the controller, the initial state has to be restricted with some condition to guarantee the convergence of the algorithm. The settle of initial condition problem has long been pursued in the ILC. There are commonly two kinds of initial condition problems: one is zero initial error problem, another is non-zero initial error problem. In practice, the repe titive operation will invariably produce excursion of the iterative initial stat e from the desired initial state. As a result, the research on the second in itial problem has more practical meaning. In this paper, for the non-zero initial error problem, one novel robust ILC alg orithms, respectively combining PD type iterative learning control algorithm wit h the robust feedback control algorithm, has been presented. This novel robust ILC algorithm contain two parts: feedforward ILC algorithm and robust feedback algorithm, which can be used to restrain disturbance from param eter variation, mechanical nonlinearities and unmodeled dynamics and to achieve good performance as well. The feedforward ILC algorithm can be used to improve the tracking error and perf ormance of the system through iteratively learning from the previous operation, thus performing the tracking task very fast. The robust feedback algorithm could mainly be applied to make the real output of the system not deviate too much fr om the desired tracking trajectory, and guarantee the system’s robustness w hen there are exterior noises and variations of the system parameter. In this paper, in order to analyze the convergence of the algorithm, Lyapunov st ability theory has been used through properly selecting the Lyapunov function. T he result of the verification shows the feasibility of the novel robust iterativ e learning control in theory. Finally, aiming at the two-freedom rate robot, simulation has been made with th e MATLAB software. Furthermore, two groups of parameters are selected to validat e the robustness of the algorithm. | TAO Li-li 1,YANG Fu-wen 2 (1. Department of Automation, University of Xiamen, Xiamen 361005, Chi na 2. Department of Electrical Engineering, University of Fuzhou, Fuzhou 350002, C hina) | 2002 | 厦门大学学报(自然科学版)2002，41，S1： | 0 |
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