14,822 research outputs found
Dynamically Stable 3D Quadrupedal Walking with Multi-Domain Hybrid System Models and Virtual Constraint Controllers
Hybrid systems theory has become a powerful approach for designing feedback
controllers that achieve dynamically stable bipedal locomotion, both formally
and in practice. This paper presents an analytical framework 1) to address
multi-domain hybrid models of quadruped robots with high degrees of freedom,
and 2) to systematically design nonlinear controllers that asymptotically
stabilize periodic orbits of these sophisticated models. A family of
parameterized virtual constraint controllers is proposed for continuous-time
domains of quadruped locomotion to regulate holonomic and nonholonomic outputs.
The properties of the Poincare return map for the full-order and closed-loop
hybrid system are studied to investigate the asymptotic stabilization problem
of dynamic gaits. An iterative optimization algorithm involving linear and
bilinear matrix inequalities is then employed to choose stabilizing virtual
constraint parameters. The paper numerically evaluates the analytical results
on a simulation model of an advanced 3D quadruped robot, called GR Vision 60,
with 36 state variables and 12 control inputs. An optimal amble gait of the
robot is designed utilizing the FROST toolkit. The power of the analytical
framework is finally illustrated through designing a set of stabilizing virtual
constraint controllers with 180 controller parameters.Comment: American Control Conference 201
Parameter reduction in nonlinear state-space identification of hysteresis
Hysteresis is a highly nonlinear phenomenon, showing up in a wide variety of
science and engineering problems. The identification of hysteretic systems from
input-output data is a challenging task. Recent work on black-box polynomial
nonlinear state-space modeling for hysteresis identification has provided
promising results, but struggles with a large number of parameters due to the
use of multivariate polynomials. This drawback is tackled in the current paper
by applying a decoupling approach that results in a more parsimonious
representation involving univariate polynomials. This work is carried out
numerically on input-output data generated by a Bouc-Wen hysteretic model and
follows up on earlier work of the authors. The current article discusses the
polynomial decoupling approach and explores the selection of the number of
univariate polynomials with the polynomial degree, as well as the connections
with neural network modeling. We have found that the presented decoupling
approach is able to reduce the number of parameters of the full nonlinear model
up to about 50\%, while maintaining a comparable output error level.Comment: 24 pages, 8 figure
Data-driven modelling of biological multi-scale processes
Biological processes involve a variety of spatial and temporal scales. A
holistic understanding of many biological processes therefore requires
multi-scale models which capture the relevant properties on all these scales.
In this manuscript we review mathematical modelling approaches used to describe
the individual spatial scales and how they are integrated into holistic models.
We discuss the relation between spatial and temporal scales and the implication
of that on multi-scale modelling. Based upon this overview over
state-of-the-art modelling approaches, we formulate key challenges in
mathematical and computational modelling of biological multi-scale and
multi-physics processes. In particular, we considered the availability of
analysis tools for multi-scale models and model-based multi-scale data
integration. We provide a compact review of methods for model-based data
integration and model-based hypothesis testing. Furthermore, novel approaches
and recent trends are discussed, including computation time reduction using
reduced order and surrogate models, which contribute to the solution of
inference problems. We conclude the manuscript by providing a few ideas for the
development of tailored multi-scale inference methods.Comment: This manuscript will appear in the Journal of Coupled Systems and
Multiscale Dynamics (American Scientific Publishers
Virtual Constraints and Hybrid Zero Dynamics for Realizing Underactuated Bipedal Locomotion
Underactuation is ubiquitous in human locomotion and should be ubiquitous in
bipedal robotic locomotion as well. This chapter presents a coherent theory for
the design of feedback controllers that achieve stable walking gaits in
underactuated bipedal robots. Two fundamental tools are introduced, virtual
constraints and hybrid zero dynamics. Virtual constraints are relations on the
state variables of a mechanical model that are imposed through a time-invariant
feedback controller. One of their roles is to synchronize the robot's joints to
an internal gait phasing variable. A second role is to induce a low dimensional
system, the zero dynamics, that captures the underactuated aspects of a robot's
model, without any approximations. To enhance intuition, the relation between
physical constraints and virtual constraints is first established. From here,
the hybrid zero dynamics of an underactuated bipedal model is developed, and
its fundamental role in the design of asymptotically stable walking motions is
established. The chapter includes numerous references to robots on which the
highlighted techniques have been implemented.Comment: 17 pages, 4 figures, bookchapte
Lyapunov based reference model of tension control in a continuous strip processing line with multi-motor drive
The article describes design and experimental verification of a new control structure with reference model for a multi-motor drive of a continuous technological line in which the motors are mutually mechanically coupled through processed material. Its principle consists in creating an additional information by introducing a new suitable state variable into the system. This helps to achieve a zero steady-state control deviation of the tension in the strip. Afterwards, the tension controller is designed to ensure asymptotic stability of the extended system by applying the second Lyapunov method. The realized experimental measurements performed on a continuous line laboratory model confirm the advantages and correctness of the proposed control structure: it is simple, stable, robust against changes of parameters, invariant to operating disturbances and ensures a high-quality dynamics of the controlled system prescribed by the reference model. To demonstrate effectiveness of the design, the performance of the controller was compared with properties of a standard Proportional Integral Derivative/Proportional Integral (PID/PI) controller designed in frequency domain
Compressed Passive Macromodeling
This paper presents an approach for the extraction of passive macromodels of large-scale interconnects from their frequency-domain scattering responses. Here, large scale is intended both in terms of number of electrical ports and required dynamic model order. For such structures, standard approaches based on rational approximation via vector fitting and passivity enforcement via model perturbation may fail because of excessive computational requirements, both in terms of memory size and runtime. Our approach addresses this complexity by first reducing the redundancy in the raw scattering responses through a projection and approximation process based on a truncated singular value decomposition. Then we formulate a compressed rational fitting and passivity enforcement framework which is able to obtain speedup factors up to 2 and 3 orders of magnitude with respect to standard approaches, with full control over the approximation errors. Numerical results on a large set of benchmark cases demonstrate the effectiveness of the proposed techniqu
Implementation Of Internal Model Control (IMC) In Continuous Distillation Column.
Distillation columns have been widely used in chemical plants for separation process. The high nonlinearity and dynamic behavior of the column make them hard to control
Direct control strategy for a four-level three-phase flying-capacitor inverter
A direct predictive control strategy is proposed for a three-phase four-level flying-capacitor (FC) inverter in this paper. The balancing of the FC voltages, a challenge in applications with small capacitors and low switching frequencies, is done without any modulation, simply using tables calculated offline. These allow the realization of fast-dynamics output currents with reduced dv/dt in the output voltages and reduced switching frequencies. Moreover, no interharmonics are created when operating at low switching frequencies and with reference currents containing multiple harmonic components, which is a key feature for active power filters. Simulations and experimental results are presented to demonstrate the excellent performance of the direct control strategy in comparison with a conventional pulsewidth-modulation control technique, mostly for operation at low switching frequencies
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