Air-Fuel Ratio Control of Spark Ignition Engines With Unknown System Dynamics Estimator: Theory and Experiments

This brief addresses the emission reduction of spark ignition engines by proposing a new control to regulate the air-fuel ratio (AFR) around the ideal value. After revisiting the engine dynamics, the AFR regulation is represented as a tracking control of the injected fuel amount. This allows to take the fuel film dynamics into consideration and simplify the control design. The lumped unknown engine dynamics in the new formulation are online estimated by suggesting a new effective unknown system dynamics estimator. The estimated variable can be superimposed on a commercially configured, well-calibrated gain scheduling like proportional-integral-differential (PID) control to achieve a better AFR response. The salient feature of this proposed control scheme lies in its simplicity and the small number of required measurements, that is, only the air mass flow rate, the pressure and temperature in the intake manifold, and the measured AFR value are used. Practical experiments on a Tata Motors Limited two-cylinder gasoline engine are carried out under a realistic driving cycle. The comparative results show that the proposed control can achieve an improved AFR control response and reduced emissions

Multi-H∞ controls for unknown input-interference nonlinear system with reinforcement learning

This article studies the multi-H∞ controls for the input-interference nonlinear systems via adaptive dynamic programming (ADP) method, which allows for multiple inputs to have the individual selfish component of the strategy to resist weighted interference. In this line, the ADP scheme is used to learn the Nash-optimization solutions of the input-interference nonlinear system such that multiple H∞ performance indices can reach the defined Nash equilibrium. First, the input-interference nonlinear system is given and the Nash equilibrium is defined. An adaptive neural network (NN) observer is introduced to identify the input-interference nonlinear dynamics. Then, the critic NNs are used to learn the multiple H∞ performance indices. A novel adaptive law is designed to update the critic NN weights by minimizing the Hamiltonian-Jacobi-Isaacs (HJI) equation, which can be used to directly calculate the multi-H∞ controls effectively by using input-output data such that the actor structure is avoided. Moreover, the control system stability and updated parameter convergence are proved. Finally, two numerical examples are simulated to verify the proposed ADP scheme for the input-interference nonlinear system

Overview of the Canadian pediatric end-stage renal disease database

<p>Abstract</p> <p>Background</p> <p>Performing clinical research among pediatric end-stage renal disease patients is challenging. Barriers to successful initiation and completion of clinical research projects include small sample sizes and resultant limited statistical power and lack of longitudinal follow-up for hard clinical end-points in most single center studies.</p> <p>Description</p> <p>Existing longitudinal organ failure disease registry and administrative health datasets available within a universal access health care system can be used to study outcomes of end-stage renal disease among pediatric patients in Canada. To construct the Canadian Pediatric End-Stage Renal Disease database, registry data were linked to administrative health data through deterministic linkage techniques creating a research database which consists of socio-demographic variables, clinical variables, all-cause hospitalizations, and relevant outcomes (death and renal allograft loss) for this patient population. The research database also allows study of major cardiovascular events using previously validated administrative data definitions.</p> <p>Conclusion</p> <p>Organ failure registry linked to health administrative data can be a powerful tool to perform longitudinal studies in pediatric end-stage renal disease patients. The rich clinical and demographic information found in this database will facilitate study of important medical and non-medical risk factors for death, graft loss and cardiovascular disease among pediatric end-stage renal disease patients.</p

Robust adaptive control for vehicle active suspension systems with uncertain dynamics

This paper proposes a new robust adaptive law for adaptive control of vehicle active suspensions with unknown dynamics (e.g. non-linear springs and piece-wise dampers), where precise estimation of essential vehicle parameters (e.g. mass of vehicle body, mass moment of inertia for the pitch motions) may be achieved. This adaptive law is designed by introducing a novel leakage term with the parameter estimation error, such that exponential convergence of both the tracking error and parameter estimation error may be proved simultaneously. Appropriate comparisons with several traditional adaptive laws (e.g. gradient and σ-modification method) concerning the convergence and robustness are presented. The mitigation of the vertical and pitch displacements can be achieved with the proposed control to improve the ride comfort. The suspension space limitation and the tyre road holding are also studied. A dynamic simulator consisting of commercial vehicle simulation software Carsim® and Matlab® is built to validate the efficacy of the proposed control scheme and to illustrate the improved estimation performance with the new adaptive law. </jats:p

Increased Hemodialysis Catheter Use in Canada and Associated Mortality Risk: Data from the Canadian Organ Replacement Registry 2001–2004

Background and objectives: The 1999 Canadian vascular access guidelines recommend the fistula as the access of choice. The study describes the trends in hemodialysis access use, variation among provinces, and the association with mortality from 2001 to 2004