Necessity Of Tuning Research Articles

Reinforcement Learning of the Prediction Horizon in Model Predictive Control

Abstract Model predictive control (MPC) is a powerful trajectory optimization control technique capable of controlling complex nonlinear systems while respecting system constraints and ensuring safe operation. The MPC’s capabilities come at the cost of a high online computational complexity, the requirement of an accurate model of the system dynamics, and the necessity of tuning its parameters to the specific control application. The main tunable parameter affecting the computational complexity is the prediction horizon length, controlling how far into the future the MPC predicts the system response and thus evaluates the optimality of its computed trajectory. A longer horizon generally increases the control performance, but requires an increasingly powerful computing platform, excluding certain control applications. The performance sensitivity to the prediction horizon length varies over the state space, and this motivated adaptive horizon model predictive control (AHMPC), which adapts the prediction horizon according to some criteria. In this paper we propose to learn the optimal prediction horizon as a function of the state using reinforcement learning (RL). We show how the RL learning problem can be formulated and test our method on two control tasks — showing clear improvements over the fixed horizon MPC scheme — while requiring only minutes of learning.

The Role of Nanomaterials in Modulating the Structure and Function of Biomimetic Catalysts.

Nanomaterial-incorporated enzyme mimics have so far been examined in various cases, and their properties are governed by the properties of both catalysts and materials. This review summarizes recent efforts in understanding the role of inorganic nanomaterials for modulating biomimetic catalytic performance. Firstly, the importance of enzyme mimics, and the necessity for tuning their catalysis will be outlined. Based on structural characteristics, these catalysts are divided into two types: traditional artificial enzymes, and novel nanomaterial-based enzyme mimics. Secondly, the mechanisms on how nano-sized materials interact with these catalysts will be examined. Intriguingly, incorporating various nanomaterials into biomimetic catalysts may provide a convenient and highly efficient method for the modulation of activities as well as stabilities or introduce new and attractive features. Finally, the perspectives of the main challenges and future opportunities in the areas of nanomaterial-incorporated biomimetic catalysis will be discussed. In this regard, nanomaterials as a kind of promising scaffold for tuning catalysis will attract more and more attention and be practically applied in numerous fields.

Accurate transonic wave drag prediction using simple physical models

A new method is presented to compute the transonic wave drag of airfoils. Coupled with an inverse boundary-layer procedure, the calculated results have an accuracy comparable to experiments. The method is robust and easy to handle without the necessity of tuning; hence, it is an excellent engineering tool for supercritical airfoil design. The inviscid flowfield is assumed to be governed by the full potential equation except at the shock. The solution is obtained by a finite-difference method. At shock points, a shock operator is introduced; it satisfies the kinematic Prandtl relation for normal and oblique shocks, which is the consistent condition for the velocity potential. For each streamline behind the shock, an entropy correction is calculated by the Rankine-Hugoniot equations. The wave drag is given by integrating the entropy rise along the shock. The computational mesh, formed by incompressibl e stream and potential lines, allows easy coupling of the boundary-layer solution at the airfoil and wake. The H-type singularity at the incompressible stagnation point is handled by a finite-volume procedure. For better physical pressure and drag solutions, the condition of the normal shock has to be altered due to the boundary layer. Therefore, an analytic model of the inviscid interference region was developed and the essential features are embedded in the numerical procedure.

TUNING THIS CURIOUS HARP.

Francis BACON in 1605 wrote... "the office of medicine is but to tune this curious harp of man's body and to reduce it to harmony." This poetic concept of the physician displays the fundamental insight that poetry achieves repeatedly as it holds the mirror to human affairs. There is today a growing awareness of the many strings in the fine instrument of man, and of the necessity for tuning them all to produce the harmony that is health. Bacon recognized his era's sad lack of knowledge concerning people and disease, but he made some amazingly prescient suggestions. Long before Thomas Sydenham was born, Bacon urged a return to the long discarded Hippocratic "diligence which used to set down a narrative... of his patients, and how they were judged by recovery or death"; he found "medicinal histories deficient." With pathology not even in its infancy, Bacon urges that the "footsteps of