Optimum kinematic design of a planar cable-driven parallel robot with wrench-closure gait trajectory

https://hal.archives-ouvertes.fr/hal-01084794/document

Determination of the Maximal Singularity-Free Workspace of 3-DOF Parallel Mechanisms with a Constructive Geometric Approach

This paper proposes a systematic algorithm based on the concept of interval analysis to obtain the maximal singularity-free circle or sphere within the workspace of parallel mechanisms. As case studies the 3-RPR planar and 6-UPS parallel mechanisms are considered to illustrate the relevance of the algorithm for 2D and 3D workspaces. To this end, the main algorithm is divided into four sub-algorithms, which eases the understanding of the main approach and leads to a more effective and robust algorithm to solve the problem. The first step is introduced to obtain the constant-orientation workspace and then the singularity locus. The main purpose is to obtain the maximal singularity-free workspace for an initial guess. Eventually, the general maximal singularity-free workspace is obtained. The main contribution of the paper is the proposition of a systematic algorithm to obtain the maximal singularity-free circle/sphere in the workspace of parallel mechanisms. The combination of a maximal singularity-free circle or sphere with the workspace analysis by taking into account the stroke of actuators, as additional constraint to the latter problem, is considered. Moreover, the center point of the circle/sphere is not restrained to a prescribed point.

/pdf/determining-the-maximal-singularity-free-circle-or-sphere-of-1x9gn7p60o.pdf

Determining the Maximal Singularity-free Circle or Sphere of Parallel Mechanisms Using Interval Analysis

Singularity-free workspace analysis of general 6-UPS parallel mechanisms via convex optimization

This paper investigates the maximal singularity-free ellipse of 3-RPR planar parallel mechanisms. The paper aims at finding the optimum ellipse, by taking into account the stroke of actuators, in which the mechanism exhibits no singularity, which is a definite asset in practice. Convex optimization is adopted for the mathematical framework of this paper which requires a matrix representation for the kinematic properties of the mechanism under study in order to solve the latter optimization problem. Based on the nature of the expressions involved in the problem, two situations may arise: dealing with either convex or non-convex expressions. Both situations are treated separately with two very fast and systematic algorithms. For the first situation, an exact method is applied while for the second one, which is a general form of the first situation, convex optimization is accompanied with an iterative procedure. The computational time for the two proposed algorithms are considerably low compared with other methods proposed in the literature which opens an avenue to use the proposed algorithms for real-time purposes.

On the maximal singularity-free ellipse of planar 3-RP R parallel mechanisms via convex optimization

This paper presents a new algorithm to find the singularity-free cylindrical workspace of parallel manipulators. Because of the limited workspace of parallel manipulators cluttered with different types of singularities, a simple and robust technique to determine continuous singularity-free zones in the workspace of parallel manipulators is required. Here, the largest singularity-free cylinder within the workspace for any prescribed orientation ranging around a reference orientation angle of moving platform is determined. To this end, Particle Swarm Optimization is utilized to find the closest point on the singularity surface to the axis of the cylinder. By implementing the algorithm on 3-RPR planar parallel manipulator, the results show that this algorithm improves the efficiency and leads to significantly larger singularity-free workspace than those reported earlier.

A new approach to determine the maximal singularity-free zone of 3-rpr planar parallel manipulator

Soft gastric simulators are the latest gastric models designed to imitate gastrointestinal (GI) functions in actual physiological conditions. They are used in in vitro tests for examining the drug and food behaviors in the GI tract. As the main motility function of the GI tract, the peristalsis can be altered in some gastric disorders, for example, by being delayed or accelerated. To simulate the stomach motility, a GI simulator must achieve a prescribed healthy or pathological peristalsis. This requires the simulator to be controlled in a closed loop. Unlike conventional controllers that stabilize a controlled plant asymptotically, a finite-time controller regulates state variables to their equilibrium points in a predetermined time interval. This article presents the design and implementation of a finite-time, model-based state feedback controller (based on the differential Riccati equation) on a soft robotic gastric simulator's actuators for the first time. We propose a mass-spring-damper model of a ring-shaped soft pneumatic actuator (RiSPA). RiSPA is a bellows-driven, elastomer-based actuator developed to reproduce motility functions of the lower part of the stomach (pyloric antrum). The proposed model is augmented by a new approach for modeling the soft tissues, where the moments of inertia of the system constituents are considered as time-varying functions. The finite-time controller is successfully applied on the RiSPA in numerical simulation and experimental implementation, and the results were thoroughly analyzed and discussed. Its accuracy and the ability to control in a predetermined time are highlighted in the tracking of peristalsis trajectory and contractive regulations.

Finite-Time Contraction Control of a Ring-Shaped Soft Pneumatic Actuator Mimicking Gastric Pathologic Motility Conditions.


 In this paper, an 
 
 
 
$\textrm{H}_{{\infty }}$

 
 dynamic output feedback controller is experimentally implemented for the position regulation of a fully actuated tilted-rotor octocopter unmanned aerial vehicle (UAV) to improve wind disturbance rejection during station-keeping. To apply the lateral forces, besides the standard tilt-to-translate (attitude-thrust) movement, tilted-rotor UAVs can generate vectored (horizontal) thrust. Vectored-thrust is high-bandwidth but saturation-constrained, while attitude-thrust generates larger forces with lower bandwidth. For the first time, this paper emphasizes the frequency-dependent allocation of weighting matrices in 
 
 
 
$\textrm{H}_{{\infty }}$

 
 control design based on the physical capabilities of the fully actuated UAV (vectored-thrust and attitude-thrust). A dynamic model of the tilted-rotor octocopter, including aerodynamic effects and rotor dynamics, is presented to design the controller. The proposed 
 
 
 
$\textrm{H}_{{\infty }}$

 
 controller solves the frequency-dependent actuator allocation problem by augmenting the dynamic model with weighting transfer functions. This novel frequency-dependent allocation utilizes the attitude-thrust for low-frequency disturbances and vectored-thrust for high-frequency disturbances, which exploits the maximum potential of the fully actuated UAV. Several wind tunnel experiments are conducted to validate the model and wind disturbance rejection performance, and the results are compared to the baseline PX4 Autopilot controller on both the tilted-rotor and a planar octocopter. The 
 
 
 
$\textrm{H}_{{\infty }}$

 
 controller is shown to reduce station-keeping error by up to 50% for an actuator usage 25% higher in free-flight tests.

Frequency-dependent control for wind disturbance rejection of a fully actuated UAV

Digital Twins (DTs) mimic a physical system using a digital version of the real system. While these have been explored in many domains, digital twins of human organs are yet to be created, especially those that are inspired by formal methods. To this end, we propose the first Cardiac Digital Twins (CDTs) by leveraging two key innovations from our research group. The first is a real-time model of the heart, that is based on a network of hybrid automata to represent the cardiac conduction system that mimics the rhythmic electrical activity of a normal heart. The model can be parametrised to exhibit disease states in real-time and this approach is being used by MathWorks for closedloop validation of pacemakers in real-time. This work has raised the interest of both device manufacturers and certification agencies, especially in the USA. Our group has expertise in digital biomarkers obtained from wearables, such as Electrocardiograms (ECGs) and Photoplethysmograms (PPGs). These provide a window into the cardiac cycle and we have already shown that the two signals are strongly correlated. Hence, a second innovation is related to using wearables to personalise the real-time heart model, so that the model generates ECGs matching that of an individual in different states. Our approach paves the way for developing personalised therapies, realtime monitoring, and accurate estimation of heart rate variability.

Tuning Into My Heart Through Wearables: Towards a Formal Cardiac Digital Twin

The soft pneumatic actuation is considered one of the most practical actuation systems in bioinspired applications, where the supplied air inflates expandable channels embedded in soft materials and causes desired movements. As the number of soft actuation applications increases, the control of soft pneumatic actuators becomes more important. This paper discusses the design and implementation of the feedback linearization control for a soft ring actuator called RiSPA. RiSPA is a bellows-driven, elastomer-based actuator that was developed to reproduce motility functions of the lower part of the stomach for a gastric simulator. The dynamics model for the RiSPA is highly nonlinear and time-varying. By applying feedback linearization, the RiSPA's dynamic model is converted into a linear time-invariant (LTI) system. Then, the linear quadratic regulator (as a linear optimal controller) is designed and applied on the new LTI model. The numerical simulation results show that the regulation performance is successfully conducted on the RiSPA model, and all the state variables have reached their desired values.

Optimal Feedback Linearization Control for a Bioinspired Soft Pneumatic Contractive Actuator

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