Current Issue : January - March Volume : 2014 Issue Number : 1 Articles : 5 Articles
The SystemsModeling Language (SysML) is a standard, general-purpose,modeling language for model-based systems engineering\r\n(MBSE). SysML supports the specification, analysis, and design of a broad range of complex systems such as control systems. The\r\nauthors demonstrate how they can integrate a SysML modeling tool (IBM Rational Rhapsody) with a proprietary simulation tool\r\n(MathWorks Simulink) and a Computer Algebra System (CAS) to validate system specification. The integration with Simulink\r\nenables users to perform systems engineering process in a SysML model, while designing continuous control algorithms and\r\nplant behavior in Simulink, and to validate the behavior by simulating the overall composition in Simulink. The integration with a\r\nCAS enables the evaluation of mathematical constraints defined in SysML parametric diagrams.The authors also show the overall\r\napproach using a Dual Clutch Transmission (DCT) and a Cruise Control System as examples....
This paper studies the application of proper orthogonal decomposition (POD) to reduce the order of distributed reactor models\r\nwith axial and radial diffusion and the implementation of model predictive control (MPC) based on discrete-time linear time\r\ninvariant (LTI) reduced-ordermodels. In this paper, the control objective is to keep the operation of the reactor at a desired operating\r\ncondition in spite of the disturbances in the feed flow. This operating condition is determined by means of an optimization algorithm\r\nthat provides the optimal temperature and concentration profiles for the system. Around these optimal profiles, the nonlinear partial\r\ndifferential equations (PDEs), that model the reactor are linearized, and afterwards the linear PDEs are discretized in space giving\r\nas a result a high-order linear model. POD and Galerkin projection are used to derive the low-order linear model that captures the\r\ndominant dynamics of the PDEs, which are subsequently used for controller design. An MPC formulation is constructed on the\r\nbasis of the low-order linear model.The proposed approach is tested through simulation, and it is shown that the results are good\r\nwith regard to keep the operation of the reactor....
In networked control systems (NCSs), the presence of communication networks in control loops causes many imperfections such\r\nas random delays, packet losses, multipacket transmission, and packet disordering. In fact, random delays are usually the most\r\nimportant problems and challenges in NCSs because, to some extent, other problems are often caused by random delays. In order\r\nto compensate for random delays which may lead to performance degradation and instability of NCSs, it is necessary to establish\r\nthe mathematical model of random delays before compensation. In this paper, four major delay models are surveyed including\r\nconstant delay model, mutually independent stochastic delay model, Markov chain model, and hidden Markov model. In each\r\ndelay model, some promising compensation methods of delays are also addressed....
This paper presents the development, experimentation, and validation of a reliable and robust system to monitor the injector pulse\r\ngenerated by an engine control module (ECM) which can easily be calibrated for different engine platforms and then feedback the\r\ncorresponding fueling quantity to the real-time computer in a closed-loop controller in the loop (CIL) bench in order to achieve\r\noptimal fueling. This research utilizes field programmable gate arrays (FPGA) and directmemory access (DMA) transfer capability\r\nto achieve high speed data acquisition and delivery. This work is conducted in two stages: the first stage is to study the variability\r\ninvolved in the injected fueling quantity from pulse to pulse, from injector to injector, between real injector stators and inductor\r\nload cells, and over different operating conditions. Different thresholds have been used to find out the best start of injection (SOI)\r\nthreshold and the end of injection (EOI) threshold that capture the injector ââ?¬Å?on-timeââ?¬Â with best reliability and accuracy. Second\r\nstage involves development of a system that interprets the injector pulse into fueling quantity. The system can easily be calibrated\r\nfor various platforms. Finally, the use of resulting correction table has been observed to capture the fueling quantity with highest\r\naccuracy....
This paper presents a backward differential flow for solving singular optimal control problems. By using Krotov equivalent\r\ntransformation, the cost functional is converted to a class of global optimization problems. Some properties of the flow are given\r\nto reveal the significant relationship between the dynamic of the flow and the geometry of the feasible set. The proposed method is\r\nalso used in solving a class of variational problems. Some examples are illustrated....
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