Periodic Motion Planning for Virtually Constrained (Hybrid) Mechanical Systems

The paper presents sufficient and almost necessary conditions for the presence of periodic solutions for zero dynamics of virtually constrained under-actuated Euler-Lagrange system. This result is further extended to detect periodic solutions for a class of hybrid systems in the plane and analyze their orbital stability and instability. Illustrative examples are given

On the Lagrangian Structure of Reduced Dynamics Under Virtual Holonomic Constraints

This paper investigates a class of Lagrangian control systems with $n$ degrees-of-freedom (DOF) and n-1 actuators, assuming that $n-1$ virtual holonomic constraints have been enforced via feedback, and a basic regularity condition holds. The reduced dynamics of such systems are described by a second-order unforced differential equation. We present necessary and sufficient conditions under which the reduced dynamics are those of a mechanical system with one DOF and, more generally, under which they have a Lagrangian structure. In both cases, we show that typical solutions satisfying the virtual constraints lie in a restricted class which we completely characterize.Comment: 23 pages, 5 figures, published online in ESAIM:COCV on April 28th, 201

Kite Generator System Periodic Motion Planning Via Virtual Constraints

International audienceThis paper presents a new control strategy for Kite Generator System (KGS). The proposed feedback strategy is based on motion planning using the virtual constraint approach and ensures exponential orbital stability of the desired trajectory. The strategy is detailed, applied and tested via numerical simulations and showed good convergence to a desired periodic motion

Control of a Bicycle Using Virtual Holonomic Constraints

The paper studies the problem of making Getz's bicycle model traverse a strictly convex Jordan curve with bounded roll angle and bounded speed. The approach to solving this problem is based on the virtual holonomic constraint (VHC) method. Specifically, a VHC is enforced making the roll angle of the bicycle become a function of the bicycle's position along the curve. It is shown that the VHC can be automatically generated as a periodic solution of a scalar periodic differential equation, which we call virtual constraint generator. Finally, it is shown that if the curve is sufficiently long as compared to the height of the bicycle's centre of mass and its wheel base, then the enforcement of a suitable VHC makes the bicycle traverse the curve with a steady-state speed profile which is periodic and independent of initial conditions. An outcome of this work is a proof that the constrained dynamics of a Lagrangian control system subject to a VHC are generally not Lagrangian.Comment: 18 pages, 8 figure

Real-Time Planning with Primitives for Dynamic Walking over Uneven Terrain

We present an algorithm for receding-horizon motion planning using a finite family of motion primitives for underactuated dynamic walking over uneven terrain. The motion primitives are defined as virtual holonomic constraints, and the special structure of underactuated mechanical systems operating subject to virtual constraints is used to construct closed-form solutions and a special binary search tree that dramatically speed up motion planning. We propose a greedy depth-first search and discuss improvement using energy-based heuristics. The resulting algorithm can plan several footsteps ahead in a fraction of a second for both the compass-gait walker and a planar 7-Degree-of-freedom/five-link walker.Comment: Conference submissio

Collision-free path planning for robots using B-splines and simulated annealing

This thesis describes a technique to obtain an optimal collision-free path for an automated guided vehicle (AGV) and/or robot in two and three dimensions by synthesizing a B-spline curve under geometric and intrinsic constraints. The problem is formulated as a combinatorial optimization problem and solved by using simulated annealing. A two-link planar manipulator is included to show that the B-spline curve can also be synthesized by adding kinematic characteristics of the robot. A cost function, which includes obstacle proximity, excessive arc length, uneven parametric distribution and, possibly, link proximity costs, is developed for the simulated annealing algorithm. Three possible cases for the orientation of the moving object are explored: (a) fixed orientation, (b) orientation as another independent variable, and (c) orientation given by the slope of the curve. To demonstrate the robustness of the technique, several examples are presented. Objects are modeled as ellipsoid type shapes. The procedure to obtain the describing parameters of the ellipsoid is also presented

Minimum-Fuel Trajectory Design in Multiple Dynamical Environments Utilizing Direct Transcription Methods and Particle Swarm Optimization

Particle swarm optimization is used to generate an initial guess for designing fuel-optimal trajectories in multiple dynamical environments. Trajectories designed in the vicinity of Earth use continuous or finite low-thrust burning and transfer from an inclined or equatorial circular low-Earth-orbit to a geostationary orbit. In addition, a trajectory from near-Earth to a periodic orbit about the cislunar Lagrange point with minimized impulsive burn costs is designed within a multi-body dynamical environment. Direct transcription is used in conjunction with a nonlinear optimizer to find locally-optimal trajectories given the initial guess. The near-Earth transfers are propagated at low-level thrust where neither the very-low-thrust spiral solution nor the impulsive transfer is an acceptable starting point. The very-high-altitude transfer is designed in a multi-body dynamical environment lacking a closed-form analytical solution. Swarming algorithms excel given a small number of design parameters.When continuous control time histories are needed, employing a polynomial parameterization facilitates the generation of feasible solutions. For design in a circular restricted three-body system, particle swarm optimization gains utility due to a more global search for the solution, but may be more sensitive to boundary constraints. Computation time and constraint weighting are areas where a swarming algorithm is weaker than other approaches

Stochastic Orbit Prediction Using KAM Tori

Kolmogorov-Arnold-Moser (KAM) Theory states that a lightly perturbed, conservative, dynamical system will exhibit lasting quasi-periodic motion on an invariant torus. Its application to purely deterministic orbits has revealed exquisite accuracy limited only by machine precision. The theory is extended with new mathematical techniques for determining and predicting stochastic orbits for Earth satellite systems. The linearized equations of motion are developed and a least squares estimating environment is pioneered to fit observation data from the International Space Station to a phase space trajectory that exhibits drifting toroidal motion over a dense continuum of adjacent tori. The dynamics near the reference torus can be modeled with time-varying torus parameters that preserve both deterministic and stochastic effects. These parameters were shown to predict orbits for days into the future without tracking updates—a vast improvement over classical methods of orbit propagation that require routine updates