Spacecraft solar arrays convert sunlight into electrical energy to fulfil the energy requirements of various missions. This work proposes a comprehensive environment for accurate power operation predictions. Specifica...
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A shift from PID control to model predictive control is noted. The fuzzy Takagi-Sugeno Kang (TSK) model provides a hybrid qualitative/quantitative knowledge representation. Its linear autoregressive rule-consequent pa...
A shift from PID control to model predictive control is noted. The fuzzy Takagi-Sugeno Kang (TSK) model provides a hybrid qualitative/quantitative knowledge representation. Its linear autoregressive rule-consequent parts facilitate the concept of adaptive estimation of their parameters. The work (parts of which are described in this paper) has shown how this can be achieved within a model-based predictive control context. This adaptive control architecture has been demonstrated on benchmark process controlsystems of a SISO nature.
Almost all existing Hammerstein system nonparametric identification algorithms can recover the unknown system nonlinear element up to an additive constant, and one functional value of the nonlinearity is usually assum...
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Almost all existing Hammerstein system nonparametric identification algorithms can recover the unknown system nonlinear element up to an additive constant, and one functional value of the nonlinearity is usually assumed to be known to make the constant solvable. To overcome this defect, in this paper, a new nonparametric polynomial identification algorithm for the Hammerstein system is proposed which extends the idea in the author's previous work on the Hammerstein system identification to a more general and practical case, where no functional value of the system nonlinearity is known a priori. Convergence and convergence rates in both uniform and global senses are established, and simulation studies demonstrate the effectiveness and advantage of the new algorithm.
Using modern nonlinear identification techniques, dose-response dynamics for two muscle relaxant trails have been obtained. A so-called NARMAX model has been found for Vecuronium applied to a dog, and Atracurium given...
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Using modern nonlinear identification techniques, dose-response dynamics for two muscle relaxant trails have been obtained. A so-called NARMAX model has been found for Vecuronium applied to a dog, and Atracurium given to a human. With the relaxant dynamics structure thus obtained, the work proceeded to the control phase. Simple three-term PID controllers were first designed with their parameters being optimised, off-line, using the Simplex method. The non-adaptive nature of this class of controllers makes their robustness open to question when the system parameters for which they have been optimised change. Hence, adaptive controllers in the form of linear and nonlinear generalised minimum variance self-tuners, generalised predictive control and nonlinear k-step ahead predictive controllers are also considered. All of these latter control approaches are shown to be satisfactory, in terms of transient and steady-state performance.
We study the effect of accumulative payoff on the evolution of cooperation in the evolutionary prisoner＇s dilemma on a square lattice. We introduce a decaying factor for the accumulative payoff, which characterizes t...
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We study the effect of accumulative payoff on the evolution of cooperation in the evolutionary prisoner＇s dilemma on a square lattice. We introduce a decaying factor for the accumulative payoff, which characterizes the extent that the historical payoff is accumulated. It is shown that for fixed values of the temptation to defect, the density of cooperators increases with the value of the decaying factor. This indicates that the more the historical payoff is involved, the more favourable cooperators become. In the critical region where the cooperator density converges to zero, cooperators vanish according to a power-law-like behaviour. The associated exponents agree approximately with the two-dimensional directed percolation and depend weakly on the value of the decaying factor.
This paper studies the evolutionary prisoner＇s dilemma game on a highly clustered community network in which the clustering coefficient and the community size can be tuned. It finds that the clustering coefficient in...
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This paper studies the evolutionary prisoner＇s dilemma game on a highly clustered community network in which the clustering coefficient and the community size can be tuned. It finds that the clustering coefficient in such a degree-homogeneous network inhibits the emergence of cooperation for the entire range of the payoff parameter. Moreover, it finds that the community size can also have a marked influence on the evolution of cooperation, with a larger community size leading to not only a lower cooperation level but also a smaller threshold of the payoff parameter above which cooperators become extinct.
Various SISO feedback control techniques have been applied successfully to muscle relaxant anaesthesia in simulations and clinical trials. SISO generalised predictive control (GPC) altogether with self-organising cont...
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Various SISO feedback control techniques have been applied successfully to muscle relaxant anaesthesia in simulations and clinical trials. SISO generalised predictive control (GPC) altogether with self-organising control using fuzzy logic theory (SOFLC) are among these techniques. A multivariable model combining muscle relaxation (paralysis) and anaesthesia (unconsciousness) has been identified. The multivariable version of GPC in its basic form as well as its different extensions to include model following and observer filter polynomials is outlined in addition to the multivariable version of SOFLC. Both of these strategies are applied to the previous model whose parameters were chosen according to a Monte-Carlo method. The robustness of both control strategies is investigated and the results presented and discussed, enabling a comparison to be made between self-adaptive and self-organising techniques. It is concluded that, when a detailed mathematical model structure is available, GPC provides better control than SOFLC.
Genetic algorithms (GA) are adaptive search techniques, based on the principles of natural genetics and natural selection, which, in controlsystemsengineering, can be used as an optimization tool or as the basis of ...
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Genetic algorithms (GA) are adaptive search techniques, based on the principles of natural genetics and natural selection, which, in controlsystemsengineering, can be used as an optimization tool or as the basis of more general adaptive systems. Following an introduction to the simple GA, important characteristics of GA are identified and control applications are described.< >
This paper proposes and gives evidence supporting a team based approach to the design and implementation of engineering curricula. It shows how such an approach allows the effective integration of many different learn...
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ISBN:
(纸本)9781627481199
This paper proposes and gives evidence supporting a team based approach to the design and implementation of engineering curricula. It shows how such an approach allows the effective integration of many different learning outcomes to give a coherent student experience. Finally, it uses examples to illustrate where the web and other technology can be invaluable tools for the delivery of a holistic curriculcum.
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