Current Issue : October - December Volume : 2016 Issue Number : 4 Articles : 6 Articles
An online robust fault detection method is presented in this paper forVAVair handling unit and its implementation. Residual-based\nEWMA control chart is used to monitor the control processes of air handling unit and detect faults of air handling unit. In order\nto provide a level of robustness with respect to modeling errors, control limits are determined by incorporating time series model\nuncertainty in EWMA control chart.The fault detection method proposed was tested and validated using real time data collected\nfrom real VAV air-conditioning systems involving multiple artificial faults. The results of validation show residual-based EWMA\ncontrol chart with designing control limits can improve the accuracy of fault detection through eliminating the negative effects of\ndynamic characteristics, serial correlation, normal transient changes of system, and time series modeling errors. The robust fault\ndetection method proposed can provide an effective tool for detecting the faults of air handling units....
Twisted-string actuation devices have been adopted in various robotic systems due to their advantages of compact size and simple\nstructure. To precisely control the displacement of such devices, a dual-direction actuating mechanism, which provides both\nextension and contraction of two strings simultaneously, must be implemented. Due to the physical properties of twisted string,\nthe actuator has problems of nonlinear length variation and cross-coupled relationships between two strings. In this study, two\ncontrollers (PID-FC and LQR-FC) were synthesized with the consideration of cross-coupling dynamics between the two axes. The\nexperimental results demonstrate the performance of both tracking and synchronization responses of these two types of controllers....
Electromagnetic parameters are important for controller design and condition monitoring of permanent magnet synchronous\nmachine (PMSM) system. In this paper, an improved comprehensive learning particle swarm optimization (CLPSO) with\nopposition-based-learning (OBL) strategy is proposed for estimating stator resistance and rotor flux linkage in surface-mounted\nPMSM; the proposed method is referred to as CLPSO-OBL. In the CLPSO-OBL framework, an opposition-learning strategy is used\nfor best particles reinforcement learning to improve the dynamic performance and global convergence ability of the CLPSO.The\nproposed parameter optimization not only retains the advantages of diversity in the CLPSO but also has inherited global exploration\ncapability of the OBL. Then, the proposed method is applied to estimate the stator resistance and rotor flux linkage of surfacemounted\nPMSM.Theexperimental results show that the CLPSO-OBL has better performance in estimating winding resistance and\nPM flux compared to the existing peer PSOs. Furthermore, the proposed parameter estimation model and optimization method\nare simple and with good accuracy, fast convergence, and easy digital implementation....
According to the characteristics ofAUVmovement, a fuzzy slidingmode controller was designed, inwhich fuzzy ruleswere adopted\nto estimate the switching gain to eliminate disturbance terms and reduce chattering. The six-degree-of-freedom model of AUV\nwas simplified and longitudinal motion equations were established on the basis of previous research. The influences of first-order\nwave force and torque were taken into consideration. The REMUS was selected to simulate the control effects of conventional\nslidingmode controller and fuzzy slidingmode controller. Simulation results show that the fuzzy slidingmode controller can meet\nthe requirements and has higher precision and stronger antijamming performances compared with conventional sliding mode\ncontroller....
High voltage gain power converters are very important in photovoltaic applications mainly due to the low output voltage of\nphotovoltaic arrays.This kind of power converters includes three or more semiconductor devices and four or more energy storage\nelements, making the dynamical analysis of the controlled system more difficult. In this paper, the boost-flyback power converter\nis controlled by peak-current mode with compensation ramp. The closed-loop analysis is performed to guarantee operation\nconditions such that a period-1 orbit is attained. The converter is considered as a piecewise linear system, and the closed-loop\nstability is determined by using themonodromymatrix, obtained by the composition of the saltationmatrixes with the solutions of\nthe dynamical equations in the linear intervals. The largest eigenvalue of the monodromy matrix gives the stability of the period-1\norbit, and a deep analysis using bifurcation diagrams let us reach a conclusion about the loss of the stability, which is experimentally\nverified. To avoid overcompensation effects, the minimum value required by the compensation ramp is obtained, and the minimum\nandmaximum values of the load resistance are found too. The system has a good transient response under disturbances in the load\nand in the input voltage....
We present a comparative study of model predictive control approaches of two-wheel steering, four-wheel steering, and a combination\nof two-wheel steering with direct yaw moment control manoeuvres for path-following control in autonomous car vehicle\ndynamics systems. Single-track mode, based on a linearized vehicle and tire model, is used. Based on a given trajectory, we drove\nthe vehicle at low and high forward speeds and on low and high road friction surfaces for a double-lane change scenario in order\nto follow the desired trajectory as close as possible while rejecting the effects of wind gusts.We compared the controller based on\nboth simple and complex bicycle models without and with the roll vehicle dynamics for different types of model predictive control\nmanoeuvres. The simulation result showed that the model predictive control gave a better performance in terms of robustness for\nboth forward speeds and road surface variation in autonomous path-following control. It also demonstrated that model predictive\ncontrol is useful to maintain vehicle stability along the desired path and has an ability to eliminate the crosswind effect....
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