Applied Mechanics and Materials Vols. 764-765

Abstract: The performance assessment of hydraulic servo systems has attracted an increasing amount of attention in recent years. However, only a few studies have focused on practical approaches in this field. A performance assessment method based on radial basis function (RBF) neural network and Mahalanobis distance (MD) is proposed in this study; the method is quantized by the performance confidence value (CV). An observer model based on RBF neural network is designed to calculate the residual error between the actual and estimated outputs. The root mean square (RMS), peak value, and average absolute value are then extracted as the features of residual error, which serve as the coordinates of the feature points. Lastly, the MD between the most recent feature point and the constructed Mahalanobis space is calculated. The condition of the system is assessed by normalizing MD into a CV. The proposed method is proven to be effective by a simulation model in which leakage faults are injected. Experimental results show that the proposed method can assess the performance of hydraulic servo systems effectively.

Abstract: All parameters are automatically extracted by the bacterial foraging particle swarm optimization (BFPSO) algorithm to approach the desired control system. Three parameterize basis function neural networks (RBFNs) model to solve the car-pole system problem. Several free parameters of radial basis functions can be automatically tuned by the direct of the specified fitness function. In additional, the proper number of radial basis functions (RBFs) of the constructed RBFNs can be chosen by the defined fitness function which takes this factor into account. The desired multiple objectives of the RBFNs control system are proposed to simultaneously approach the smaller errors with a fewer RBFs number. Simulations show that the developed RBFNs control systems efficiently achieve the desired the setting lot as soon as possible.

Abstract: In this paper, the robust H∞ stabilization problem for Takagi-Sugeno fuzzy control systemswith state and input delays is explored. Based on a Lyapunov-Krasoviskii function, the delaydependentstabilization conditions are proposed in terms of linear matrix inequalities (LMIs) to guaranteethe asymptotic stabilization of time-delay Takagi-Sugeno fuzzy systems with disturbance input.Finally, a numerical example is illustrated to demonstrate the feasibility and effectiveness of the proposed stabilization.

Abstract: In this paper, the robust control problem of output dynamic observer-based control for a class of uncertain neutral systems with discrete and distributed time delays is considered. Linear matrix inequality (LMI) optimization approach is used to design the new output dynamic observer-based controls. Three classes of observer-based controls are proposed and the maximal perturbed bound is given. Based on the results of this paper, the constraint of matrix equality is not necessary for designing the observer-based controls.

Abstract: The study proposed adaptive wavelet neural network controller can achieve good and precise welding control performance and use synchrotron radiation research center developed multi-gun group automatic welding system to verify the validity of the research method. Multi-gun group welding system is applied in Taiwan Photon Source (TPS). Storage ring aluminum alloy vacuum chamber of Taiwan Photon Source .In the past aluminum alloy vacuum chamber welding, it all depends on the empirical welding rule of operator to give appropriate welding current, argon flow, wire feed speed and welding speed for control. Therefore, the paper uses automatic welding skill, which takes National Instruments PXI-8180 system as basic structure, and adaptive wavelet neural network controlled four optimized parameters, I.E. welding current, wire feed speed, flow rate of argon gas and welding speed, The vacuum chamber pressure value is also up to 6.2X10-10Torr/mA. It is successfully applied to the TPS system. Therefore, it can prove the effectiveness and practicality of the method proposed in this study.

Abstract: This research designs a web-based supervisory control system based on Raspberry Pi. The system consists of one Raspberry Pi single-board computer and multiple data acquisition modules. The sensing and driving of the system are completed by reading/writing those data modules through RS485 interface by Modbus RTU protocol. Embedded database is used to store input/output data. Embedded web server provides interface for remote monitoring and control. The system was applied to environment control for computer room. It monitors air-conditioning systems, room temperature and humidity, fire alarm systems, uninterruptible power supply (UPS) systems, electricity supply systems and door access control systems. If something happens, it can drive buzzer, alarm, voice dialing, or air conditioning. The focus of this paper is using software to integrate hardware available in the market to form a low cost reliable supervisory control system.

Abstract: This paper presents an automatic prediction model for ground vibration induced by Taiwan high-speed trains on embankment structures. The prediction model is developed using different field-measured ground vibration data. The main characteristics that affect the overall vibration level are established based on the database of measurement results. The influence factors include train speed, ground condition, measurement distance, and supported structure. Support vector machine (SVM) algorithm, a widely used prediction model, is adopted to predict the vibration level induced by high-speed trains on embankments. The measured and predicted vibration levels are compared to verify the reliability of the prediction model. Analysis results show that the developed SVM model can reasonably predict vibration level with an accuracy rate of 72% to 84% for four types of vibration level, including overall, low, middle, and high frequency ranges. The methodology in developing the automatic prediction system for ground vibration level is also presented in this paper.

Abstract: A socket information retrieval mechanism and information retrieving agent services on the basis of injection machines is proposed in this research. The proposed agent adapted customized packet format for client-server connection communication, and sent process parameters back to production process database constructed by this Institute. The production process data of injection machines can be accessed by the agent services pro-posed in any networking environment through standard services to construct a variety of systems for machine monitoring and information analysis. If an error occurs, remote machine diagnosis can be executed at once.

Abstract: This paper studies the dynamic feedrate control problem for mechanical stages performing contouring actions. In modern researches, feedrate is considered as a dynamic factor instead of simple constant value in the traditional methods, and should be properly controlled to meet higher precision standard nowadays. To incorporate the dynamic feedrate in the path interpolation, the so called non-uniform rational B-spline (NURBS) algorithm is utilized to form the fundamental real-time interpolation structure of this research. The result of a sophisticated intelligent feedrate control design is then proposed where the system feedrate is real-time determined based on both the feedback of the path curvature and the measured contour error. Experiments and comparative studies for free-form paths are also conducted where the results show that the proposed design indeed can provide significant precision improvement in overall contouring performance in contrast to the traditional method. Therefore, the effectiveness and the goal of the proposed method can be verified which suggests that the entire scheme has the potential for real industrial applications.

Abstract: This paper develops an Adaptive fuzzy sliding-mode control system algorithm for active heat dissipation system. In the proposed intelligent controller, The adaptive laws adjust the parameters of the fuzzy logic system on-line based on a Lyapunov function, so that the stability of the system can be guaranteed. Additionally, an error estimation mechanism is investigated to estimate the bound of the approximation error. Based on NI-PXI system, this research combined the (TEC) with a duct heater. It designed a smart control system featured by the new active heat dissipation system. It has been proved that this research proposes the ideas of the active heat dissipation adaptive fuzzy sliding-mode control system which may reach a good condition provided with correct temperature control function. To be more precisely, that can be easily adaptive to any environment. It is equipped with a good capability of tracking and searching.