Lie-Group Modeling and Numerical Simulation of a Helicopter

Helicopters are extraordinarily complex mechanisms. Such complexity makes it difficult to model, simulate and pilot a helicopter. The present paper proposes a mathematical model of a fantail helicopter type based on Lie-group theory. The present paper first recalls the Lagrange–d’Alembert–Pontryagin principle to describe the dynamics of a multi-part object, and subsequently applies such principle to describe the motion of a helicopter in space. A good part of the paper is devoted to the numerical simulation of the motion of a helicopter, which was obtained through a dedicated numerical method. Numerical simulation was based on a series of values for the many parameters involved in the mathematical model carefully inferred from the available technical literature.

Do generalized draw-down times lead to better dividends? A Pontryagin principle-based answer

In the context of maximizing cumulative dividends under barrier policies, generalized Azéma–Yor (draw-down) stopping times receive increasing attention during these past years. Based on Pontryagin’s maximality principle, we illustrate the necessity of such generalizations under the framework of spectrally negative Markov processes. Roughly speaking, starting from the explicit expression of the optimal value of discounted dividends in terms of the scale functions, we write down the optimality conditions (via Pontryagin’s principle). The use of generalized draw-downs is then quantified through a structure term (linked to the existence of non bang-bang optimal controls). We thoroughly study several classes of Lévy processes (Bertoin, Lévy Processes, vol. 121. Cambridge University Press, 1998; Kyprianou, Fluctuations of Lévy Processes with Applications: Introductory Lectures. Springer Science & Business Media, 2014) constituting the usual models of insurance claims and a particular piece-wise deterministic Markov model (extending the premium rate to reserve-dependent settings). In all these models, we disprove the consistency of the aforementioned structure equation, thus denying the necessity of such generalizations. We end the paper with some heuristics on possible non-trivial cases for general Markov models.

Path planning in a Riemannian manifold using optimal control

We consider the motion planning of an object in a Riemannian manifold where the object is steered from an initial point to a final point utilizing optimal control. Considering Pontryagin Minimization Principle we compute the Optimal Controls needed for steering the object from initial to final point. The Optimal Controls were solved with respect to time [Formula: see text] and shown to have norm [Formula: see text] which should be the case when the extremal trajectories, which are the solutions of Pontryagin Principle, are arc length parametrized. The extremal trajectories are supposed to be the geodesics on the Riemannian manifold. So we compute the geodesic curvature and the Gaussian curvature of the Riemannian structure.

Constrained Optimal Control of A Fractionally Damped Elastic Beam

This work presents the constrained optimal control of a fractionally damped elastic beam in which the damping characteristic is described with the Caputo fractional derivative of order 1/2. To achieve the optimal control that involves energy optimal control index with fixed endpoints, the fractionally damped elastic beam problem is first converted to a state space form of order 1/2 by using a change of coordinates. Then, the state and the costate equations are set in terms of Hamiltonian formalism and the constrained control law is acquired from Pontryagin Principle. The numerical solution of the problem is obtained with Grünwald-Letnikov approach by utilizing the link between the Riemann-Liouville and the Caputo fractional derivatives. Application of the formulations is demonstrated with an example and the illustrations are figured by MATLAB. Also, the effectiveness of the Grünwald-Letnikov approach is exhibited by comparing it with an iterative method which is one-step Adams-Bashforth-Moulton method.

KENDALI OPTIMAL PERTUMBUHAN POPULASI ECENG GONDOK DENGAN IKAN GRASS CRAP DAN PEMANENAN

Water hyacinth is a wild aquatic plant that grows quickly. The growth of water hyacinth need to be controled to prevent the flood and not to disturb paddy irrigation channels. Grass carp as herbivorous fish is used as natural predator to reduce the population of water hyacinth. The interaction between water hyacinth and grass carp is modeled using the prey-predator system. In this model there are harvest factors and predation factors using Holling type III. The optimal control problem is applied to minimize the mass of water hyacinth and harvest efforts of water hyacinth and maximize the mass of grass carp. The solution uses the Pontryagin Principle. The result is the harvesting of water hyacinth and the grass carp can minimize the water hyacinth biomass at the end of time. Eceng gondok merupakan tanaman liar di perairan yang tumbuh dengan cepat. Pertumbuhannya perlu dikendalikan agar tidak menyebabkan banjir dan tidak mengganggu saluran irigasi persawahan. Ikan grass carp sebagai ikan herbivora digunakan sebagai predator alami untuk mengurangi populasi eceng gondok. Hubungan antara eceng gondok dan ikan grass carp dimodelkan dengan menggunakan sistem prey-predator. Pada model ini terdapat faktor pemanenan dan faktor predasi menggunakan Holling tipe III. Masalah kendali optimal diterapkan dengan tujuan untuk meminimumkan massa eceng gondok dan usaha pemanenan eceng gondok serta memaksimumkan massa ikan grass carp. Penyelesaiannya menggunakan Prinsip Pontryagin. Hasilnya dengan adanya usaha pemanenan eceng gondok dan pengadaan ikan grass carp dapat meminimumkan biomassa eceng gondok di waktu akhir.

ANALISIS KESTABILAN DAN KONTROL OPTIMAL MODEL LESLIE-GOWER FUNGSI RESPON HOLLING III DENGAN PEMANENAN PADA POPULASI PREDATOR DAN PREY

This article modified the leslie-gower model on harvesting with predator and prey population. This study aims at construct a modification of leslie-gower model with holing III response function. In addition, there is an effort harvesting in predator and prey population, analyzing an equilibrium point, finding bionomic equilibrium and the condition where the present value is maximum from net income by controlling harvesting in both populations. In the modified leslie-gower model there is an equilibrium point which is asymptotically stable and when there have harvesting, the equilibrium point is also asymptotically stable. Bionomic equilibrium from harvesting on the modified leslie-gower model is maximizing the profit function π of harvesting on a model with the maximum pontryagin principle resulting an optimal equilibrium) affected by instantaneous rate of discount δ.