1,356,147 research outputs found
On-Line, Auto-Tuning Control of Electronic Expansion Valves
No full textIn this paper, the results of a research project aimed at deriving simple, high-performance,
auto-tuning, robust control algorithms for evaporators controlled by means of EEVs
(Electronic Expansion Valves) are reported. Control design is performed by resorting to
a detailed virtual prototyping environment described in Beghi and Cecchinato (2009). The
proposed control scheme consists of two nested loops. In the inner loop, the plant is
connected in feedback to a PID controller. It is assumed that the structure of the process
model is given but its parameters are unknown. The outer loop is composed of a parameter
estimator and an adaptation algorithm that updates the parameters of the PID controller
on the basis of the result of a system identification procedure. Performance of the proposed
controller is evaluated in the virtual prototyping environment by means of simulations
A property of the Routh table and its use
No full textStarting from a given polynomial, the Routh algorithm recursively generates a family of all-pole transfer functions with the same energy of the impulse response and a suitable number of its derivatives. It is shown that each of these energies is given by a linear combination of some of the others according to the entries of a row of the Routh table for the given polynomial. This fact can be exploited to evaluate certain quadratic integrals in an efficient wa
A virtual rider for motorcycles: Maneuver regulation of a multibody vehicle model
No full textThis work develops a virtual rider that can be used to
make a multi-body two-wheeled vehicle follow a specified ground
path with a prescribed velocity profile. The virtual rider system
is based on a simplified motorcycle model, the sliding plane motorcycle,
which is composed of a single rigid body with two ground
contact points. This reduced order nonlinear system was presented
in an earlier work, together with a dynamic inversion procedure
for computing a state-control trajectory corresponding to the desired
task. This dynamic inversion procedure is combined in this
work with a maneuver regulation controller to yield a nonlinear
feedback control strategy. A transverse coordinate system that is
consistent with the mechanical symmetries of ground vehicles is
constructed and used in the development of the maneuver regulation
controller. An inverse optimal control strategy, which also
exploits the mechanical symmetries, is developed to shape the dynamic
response of the closed loop system. Numerical results with
the virtual rider driving amulti-body vehicle through a demanding
maneuver with lateral accelerations reaching 1 g are presented
A deep learning-based approach to anomaly detection with 2-dimensional data in manufacturing
No full textIn modern manufacturing scenarios, detecting anomalies in production systems is pivotal to keep high-quality standards and reduce costs. Even in the Industry 4.0 context, real-world monitoring systems are often simple and based on the use of multiple univariate control charts. Data-driven technologies offer a whole range of tools to perform multivariate data analysis that allow to implement more effective monitoring procedures. However, when dealing with complex data, common data-driven methods cannot be directly used, and a feature extraction phase must be employed. Feature extraction is a particularly critical operation, especially in anomaly detection tasks, and it is generally associated with information loss and low scalability. In this paper we consider the task of Anomaly Detection with two-dimensional, image-like input data, by adopting a Deep Learning-based monitoring procedure, that makes use of convolutional autoencoders. The procedure is tested on real Optical Emission Spectroscopy data, typical of semiconductor manufacturing. The results show that the proposed approach outperforms classical feature extraction procedures
A dynamic inversion approach to motorcycle trajectory exploration
No full textRecently developed optimization and nonlinear control
strategies are applied to ride a multi-body motorcycle model
along a specified path with an associated velocity profile. The
resulting control scheme is based on three main pillars: a
dynamic inversion procedure to compute the input-state trajectories
corresponding to a desired maneuvering task, an inverse
optimal control heuristic for designing closed loop dynamics,
and a maneuver regulation controller to overcome limitations of
standard trajectory tracking scheme. The controller (virtual rider)
is implemented on a commercial simulation software. Simulation
results are presented
Trajectory exploration of a rigid motorcycle model
No full textThis paper introduces a rigid motorcycle model that
captures many important aspects of real motorcycle dynamics including
sliding and load transfer. The model is used to demonstrate
a dynamic inversion procedure which maps a desired flatland trajectory
into a corresponding (state-input) trajectory for the rigid
motorcycle model. This inverse trajectory is the solution of an optimal
control problem that is computed using the projection operator
approach for the optimization of trajectory functionals, a recently
developed optimization technique. The effectiveness of the
proposed strategy is illustrated using a trajectory computation for
a realistic path that is traversed with a demanding speed profile.
The rigid motorcycle model detailed in this paper is also of interest
as a nontrivial example of a mechanical system with nonideal holonomic
constraints
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