1,477 research outputs found
Grey-box Modelling of a Household Refrigeration Unit Using Time Series Data in Application to Demand Side Management
This paper describes the application of stochastic grey-box modeling to
identify electrical power consumption-to-temperature models of a domestic
freezer using experimental measurements. The models are formulated using
stochastic differential equations (SDEs), estimated by maximum likelihood
estimation (MLE), validated through the model residuals analysis and
cross-validated to detect model over-fitting. A nonlinear model based on the
reversed Carnot cycle is also presented and included in the modeling
performance analysis. As an application of the models, we apply model
predictive control (MPC) to shift the electricity consumption of a freezer in
demand response experiments, thereby addressing the model selection problem
also from the application point of view and showing in an experimental context
the ability of MPC to exploit the freezer as a demand side resource (DSR).Comment: Submitted to Sustainable Energy Grids and Networks (SEGAN). Accepted
for publicatio
Optimal Control of Legged-Robots Subject to Friction Cone Constraints
A hierarchical control architecture is presented for energy-efficient control
of legged robots subject to variety of linear/nonlinear inequality constraints
such as Coulomb friction cones, switching unilateral contacts, actuator
saturation limits, and yet minimizing the power losses in the joint actuators.
The control formulation can incorporate the nonlinear friction cone constraints
into the control without recourse to the common linear approximation of the
constraints or introduction of slack variables. A performance metric is
introduced that allows trading-off the multiple constraints when otherwise
finding an optimal solution is not feasible. Moreover, the projection-based
controller does not require the minimal-order dynamics model and hence allows
switching contacts that is particularly appealing for legged robots. The
fundamental properties of constrained inertia matrix derived are similar to
those of general inertia matrix of the system and subsequently these properties
are greatly exploited for control design purposes. The problem of task space
control with minimum (point-wise) power dissipation subject to all physical
constraints is transcribed into a quadratically constrained quadratic
programming (QCQP) that can be solved by barrier methods
Keep Rollin' - Whole-Body Motion Control and Planning for Wheeled Quadrupedal Robots
We show dynamic locomotion strategies for wheeled quadrupedal robots, which
combine the advantages of both walking and driving. The developed optimization
framework tightly integrates the additional degrees of freedom introduced by
the wheels. Our approach relies on a zero-moment point based motion
optimization which continuously updates reference trajectories. The reference
motions are tracked by a hierarchical whole-body controller which computes
optimal generalized accelerations and contact forces by solving a sequence of
prioritized tasks including the nonholonomic rolling constraints. Our approach
has been tested on ANYmal, a quadrupedal robot that is fully torque-controlled
including the non-steerable wheels attached to its legs. We conducted
experiments on flat and inclined terrains as well as over steps, whereby we
show that integrating the wheels into the motion control and planning framework
results in intuitive motion trajectories, which enable more robust and dynamic
locomotion compared to other wheeled-legged robots. Moreover, with a speed of 4
m/s and a reduction of the cost of transport by 83 % we prove the superiority
of wheeled-legged robots compared to their legged counterparts.Comment: IEEE Robotics and Automation Letter
Constraint-based synthesis of shape-morphing compliant structures in virtual reality
The purpose of this research is to establish a novel approach to the design of compliant shape-morphing structures using constraint-based design methods (CBDM) and virtual reality (VR). Compliant mechanisms, as opposed to rigid link mechanisms, achieve motion guidance via the compliance and deformation of the mechanism\u27s members. They are currently being explored as structural components to produce shape changes in products such as aircraft wing and antenna reflectors. The goal is to design a single-piece flexible structure capable of morphing a given curve or profile into a target curve or profile while utilizing the minimum number of actuators.
The successful design of compliant mechanisms requires an understanding of solid mechanics (deformation, stress, strain, etc.) and mechanism kinematics (properties of motion). As a result, only a fairly narrow, experienced group of engineers are successful in designing these mechanisms. This approach was developed as an alternative to the two primary methods prevalent in the design community at this time - the pseudo-rigid body method (PRBM) and the topological synthesis (which tend to suffer from either a poor potential solution synthesis capabilities or from susceptibility to overly-complex solutions). A tiered design method that relies on kinematics, finite element analysis, and optimization in order to apply the CBDM concepts to the design and analysis of shape-morphing compliant structures is presented. By segmenting the flexible element that comprises the active shape surface at multiple points in both the initial and the target configurations and treating the resulting individual elements as rigid bodies that undergo a planar or general spatial displacement we are able to apply the traditional kinematics theory to rapidly generate sets of potential solutions. An FEA-augmented optimization sequence establishes the final compliant design candidate. Coupled with a virtual reality interface and a force-feedback device this approach provides the ability to quickly specify and evaluate multiple design problems in order to arrive at the desired solution without an excessive number of design iterations and a heavy dependence on the intermediate physical prototypes
Differentiable Optimization Based Time-Varying Control Barrier Functions for Dynamic Obstacle Avoidance
Control barrier functions (CBFs) provide a simple yet effective way for safe
control synthesis. Recently, work has been done using differentiable
optimization (diffOpt) based methods to systematically construct CBFs for
static obstacle avoidance tasks between geometric shapes. In this work, we
extend the application of diffOpt CBFs to perform dynamic obstacle avoidance
tasks. We show that by using the time-varying CBF (TVCBF) formulation, we can
perform obstacle avoidance for dynamic geometric obstacles. Additionally, we
show how to extend the TVCBF constraint to consider measurement noise and
actuation limits. To demonstrate the efficacy of our proposed approach, we
first compare its performance with a model predictive control based method and
a circular CBF based method on a simulated dynamic obstacle avoidance task.
Then, we demonstrate the performance of our proposed approach in experimental
studies using a 7-degree-of-freedom Franka Research 3 robotic manipulator
Modeling and Control of Robot-Structure Coupling During In-Space Structure Assembly
This paper considers the problem of robot-structure coupling dynamics during in-space robotic assembly of large flexible structures. A two-legged walking robot is used as a construction agent, whose primary goal is to stably walking on the flexible structure while carrying a substructure component to a designated location. The reaction forces inserted by the structure to the walking robot are treated as bounded disturbance inputs, and a trajectory tracking robotic controller is proposed that combines the standard full state feedback motion controller and an adaptive controller to account for the disturbance inputs. In this study, a reduced-order Euler-Bernoulli beam structure model is adapted, and a finite number of co-located sensors and actuators are distributed along the span of the beam structure. The robot-structure coupling forces are treated as a bounded external forcing function to the structure, and hence an output covariance constraint problem can be formulated, in terms of linear matrix inequality, for optimal structure control by utilizing the direct output feedback controllers. The numerical simulations show the effectiveness of the proposed robot-structure modeling and control methodology
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