Abstract: This paper investigates an efficient combustion modeling for cycle simulation of internal combustion engine (ICE) studies. The term “efficient model” means that the models must generate desired simulation results while having fast simulation time. In other words, the efficient model is defined based on the application of the model. The objective of this study is to develop math-based models for control applications or shortly control-oriented models. This study compares different modeling approaches used to model the ICEs such as mean-value models, zero dimensional, quasi-dimensional, and multi-dimensional models for control applications. Mean-value models have been widely used for model-based control applications, but recently by developing advanced simulation tools (e.g. Maple/MapleSim) the higher order models (more complex) could be considered as control-oriented models. This paper presents the enhanced zero-dimensional cycle-by-cycle modeling and simulation of a spark ignition engine with a two-zone combustion model. The simulation results are cross-validated against the simulation results from GT-Power package and show a good agreement in terms of trends and values.
Abstract: A novel hybrid model of the lumbar spine, allowing
fast static and dynamic simulations of the disc pressure
and the spine mobility, is introduced in this work. Our
contribution is to combine rigid bodies, deformable finite
elements, articular constraints, and springs into a unique model
of the spine. Each vertebra is represented by a rigid body
controlling a surface mesh to model contacts on the facet
joints and the spinous process. The discs are modeled using
a heterogeneous tetrahedral finite element model. The facet
joints are represented as elastic joints with six degrees of
freedom, while the ligaments are modeled using non-linear
one-dimensional elastic elements. The challenge we tackle
is to make these different models efficiently interact while
respecting the principles of Anatomy and Mechanics.
The mobility, the intradiscal pressure, the facet joint force and
the instantaneous center of rotation of the lumbar spine are
validated against the experimental and theoretical results of
the literature on flexion, extension, lateral bending as well as
axial rotation.
Our hybrid model greatly simplifies the modeling task and
dramatically accelerates the simulation of pressure within the
discs, as well as the evaluation of the range of motion and the
instantaneous centers of rotation, without penalizing precision.
These results suggest that for some types of biomechanical
simulations, simplified models allow far easier modeling and
faster simulations compared to usual full-FEM approaches
without any loss of accuracy.
Abstract: Robot manipulators are highly coupled nonlinear
systems, therefore real system and mathematical model of dynamics
used for control system design are not same. Hence, fine-tuning of
controller is always needed. For better tuning fast simulation speed
is desired. Since, Matlab incorporates LAPACK to increase the speed
and complexity of matrix computation, dynamics, forward and
inverse kinematics of PUMA 560 is modeled on Matlab/Simulink in
such a way that all operations are matrix based which give very less
simulation time. This paper compares PID parameter tuning using
Genetic Algorithm, Simulated Annealing, Generalized Pattern Search
(GPS) and Hybrid Search techniques. Controller performances for all
these methods are compared in terms of joint space ITSE and
cartesian space ISE for tracking circular and butterfly trajectories.
Disturbance signal is added to check robustness of controller. GAGPS
hybrid search technique is showing best results for tuning PID
controller parameters in terms of ITSE and robustness.