Abstract:
A process is disclosed for selectively adsorbing nitrogen from a less strongly adsorbed other gas component (preferably oxygen), comprising: contacting the gas mixture in an adsorption zone with an adsorbent comprising a large-pored molecular sieve containing at least one octahedral site comprising titanium and at least silicon as a tetrahedral site. The process is particularly useful in air separation using ETS-10 as the adsorbent.
Abstract:
Improved machining of various materials is disclosed by means of a material cutting insert having an internal fluid passageway which discharges a high velocity fluid jet stream in a particular manner. An improved method for use of said cutting insert is also disclosed along with apparatus employing the improvement.
Abstract:
A process for sizing two-dimensional nanostructures includes providing the nanostructures to a liquid-liquid interface, providing probe particles to the liquid-liquid interface, obtaining an image of the nanostructures and the probe particles, and processing the image to ascertain a size property of the nanostructures.
Abstract:
An article (e.g., an interbody device) contains a polymer (e.g., polyetheretherketone (PEEK)) and transition metal-doped amorphous magnesium phosphate.
Abstract:
A method for producing an aligned boron nitride nanotube film includes drying a dispersion containing boron nitride nanotubes, a biopolymer, and a solvent.
Abstract:
During the process of coagulation, prothrombin is activated to α-thrombin by prothrombinase. Key residues in the structure of prothrombin allow for modulation of the activation of prothrombin. In certain embodiments, a recombinant prothrombin with at least one point mutation or deletion is provided.
Abstract:
Controller scaling and parameterization are described. Techniques that can be improved by employing the scaling and parameterization include, but are not limited to, controller design, tuning and optimization. The scaling and parameterization methods described here apply to transfer function based controllers, including PID controllers. The parameterization methods also applies to state feedback and state observer based controllers, as well as linear active disturbance rejection controllers. It is emphasized that this abstract is provided to comply with the rules requiring an abstract that will allow a searcher or other reader to quickly ascertain the subject matter of the application. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims.
Abstract:
Multiple designs, systems, methods and processes for controlling a system or plant using an extended active disturbance rejection control (ADRC) based controller are presented. The extended ADRC controller accepts sensor information from the plant. The sensor information is used in conjunction with an extended state observer in combination with a predictor that estimates and predicts the current state of the plant and a co-joined estimate of the system disturbances and system dynamics. The extended state observer estimates and predictions are used in conjunction with a control law that generates an input to the system based in part on the extended state observer estimates and predictions as well as a desired trajectory for the plant to follow.
Abstract:
Multiple designs, systems, methods and processes for controlling a system or plant using an extended active disturbance rejection control (ADRC) based controller are presented. The extended ADRC controller accepts sensor information from the plant. The sensor information is used in conjunction with an extended state observer in combination with a predictor that estimates and predicts the current state of the plant and a co-joined estimate of the system disturbances and system dynamics. The extended state observer estimates and predictions are used in conjunction with a control law that generates an input to the system based in part on the extended state observer estimates and predictions as well as a desired trajectory for the plant to follow.
Abstract:
An industrial controller implements a closed-loop control technique referred to as generic PID control, or GPID, which makes explicit the basic principles and methods of quantitatively combining the past, present and future in controller design and tuning. Generic PID control is backward compatible in design and in tuning with current industrial control software interfaces, and as such can be easily adopted onto existing control systems. Generic PID is also widely applicable to artificial intelligence (AI) and data analytics, such as machine learning, where error-correction is core to all algorithms.