B-spline neural networks based PID controller for Hammerstein systems

A new PID tuning and controller approach is introduced for Hammerstein systems based on input/output data. A B-spline neural network is used to model the nonlinear static function in the Hammerstein system. The control signal is composed of a PID controller together with a correction term. In order to update the control signal, the multi-step ahead predictions of the Hammerstein system based on the B-spline neural networks and the associated Jacobians matrix are calculated using the De Boor algorithms including both the functional and derivative recursions. A numerical example is utilized to demonstrate the efficacy of the proposed approaches

B-spline neural networks based PID controller for Hammerstein systems

A new PID tuning and controller approach is introduced for Hammerstein systems based on input/output data. A B-spline neural network is used to model the nonlinear static function in the Hammerstein system. The control signal is composed of a PID controller together with a correction term. In order to update the control signal, the multi-step ahead predictions of the Hammerstein system based on the B-spline neural networks and the associated Jacobians matrix are calculated using the De Boor algorithms including both the functional and derivative recursions. A numerical example is utilized to demonstrate the efficacy of the proposed approaches

Model-reference adaptive control applied to load-following of a space-nuclear power system

Nuclear power systems are presently being investigated as an alternative for both commercial and military space power systems because of their projected longevity of 7 to 10 years, their mass advantage over other space power sources at powers above approximately 25 kW{sub e}, and their ability to operate without direct illumination from the sun. These space-nuclear power systems are being designed to supply from tens of kilowatts to multimegawatts of power for continuous operation of seven years and more. Space-nuclear power systems designs that meet these requirements will not be available for refueling or maintenance during their lifetime. To ensure that the space-nuclear power system will operate safely and will respond in a predictable and desired manner, the design of the system's controller must account for changes in the system parameters over its lifetime. This paper applies model-reference adaptive control to an increase in the power demand by the load. A model-reference adaptive controller will force the actual space-nuclear power system to follow the predictable and desired response of a reference model, despite changes in the actual system's operating parameters. Included in this paper are the model-reference adaptive control algorithm, the description of the computer simulation of a space-nuclear power system and the reference model, and results that demonstrate the application of model-reference adaptive control to a change in the load power demand. The results demonstrate that model-reference adaptive control can ensure the transient response of the system despite differences between the design of the system and the as-built system as well as for variations in the systems parameters. 5 refs., 3 figs

Collections & Connections

This is the Spring-Summer 2012 issue of the bi-annual WKU Libraries newsletter Collections & Connections. This issue features the 2012 Southern Kentucky Book Fest and its related events such as the Kentucky Writers Conference. Feature stories also include the opening ceremony of the Elizabethtown/Radcliff/Ft. Knox Library, the Far Away Places and Kentucky Live talk series, the new art installation in the Helm and Cravens Library, the US Bank Art Show, the Java City noon concerts, and the Richardson Quilt Gallery Opening. In this issue, the WKU College Faculty Award and the WKU Library and University Experience Undergraduate Research Award recipients are also reported. Last but not the least is the news of a retiree from the WKU Libraries