Adjoint different equations of a system

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In summary, the conversation discusses a problem with solving the adjoint differential equations for an atmospheric reentry optimization problem. The purpose of the problem is to find the control history for alpha that results in reaching a target range within operational and terminal constraints. The equations used for velocity, range, flight-path angle, and penalty functions are mentioned, as well as the need for information on how changes in the range and penalty functions relate to the control program. The solution for this is to find special solutions to the adjoint differential equations, but the initial value is not mentioned in the paper. The control program is updated using the initial value and the change in the control program. The individual is asking for help with solving the adjoint differential equations in order to
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roldy
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I'm working on an atmospheric reentry optimization problem that I found in a paper. The purpose is to find the control history for alpha (attack angle) that results in reaching the target range ([itex]\phi[/itex]) within operational constraints and terminal constraints.

I'm using 3-DOF equations for velocity, range, and flight-path angle(θ) as well as 2 additional equations for a pilot penalty function (g-loading) and altitude penalty function (if capsule skips out above a predefined threshold, which it doesn't for this simulation). The pdf document that I am referencing is found here.

The problem I am encountering solving for the adjoint different equations (see page 30-33). Could someone explain what these are and how to get them? The paper says that I need to get information on how a change in the range, pilot penalty, and altitude penalty are related to [itex]\delta \alpha[/itex](t), the change in the control program and this is done by finding special solutions to the adjoint differential equations of the system. The paper has these differential adjoint equations but they don't mention how to find the initial value of the adjoint differential equation. The control program is updated as follows:

[itex]\alpha_1(t) = \alpha_0(t) + \delta \alpha(t)[/itex]
 
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I need to know how to solve the adjoint differential equations in order to calculate the required information. Any help would be greatly appreciated!
 

Related to Adjoint different equations of a system

1. What is an adjoint differential equation?

An adjoint differential equation is a mathematical tool used in the analysis of systems of differential equations. It is a modified version of the original system of equations that is used to determine the sensitivity of the system's solution to changes in its parameters or initial conditions.

2. How is an adjoint differential equation different from a regular differential equation?

The main difference between an adjoint differential equation and a regular differential equation is that the adjoint equation contains additional terms that represent the sensitivity of the system's solution. These terms are derived from the original system of equations and are used to analyze the effects of perturbations in the system's parameters or initial conditions.

3. What is the purpose of using adjoint differential equations?

The main purpose of using adjoint differential equations is to analyze the sensitivity of a system's solution to changes in its parameters or initial conditions. This information can be used to optimize the system's performance, design control strategies, and improve the system's stability.

4. How are adjoint differential equations solved?

Adjoint differential equations are typically solved using numerical methods, such as finite difference or finite element methods. These methods involve discretizing the equations into a set of algebraic equations that can be solved using iterative techniques. Advanced numerical methods, such as adjoint sensitivity analysis, can also be used to solve adjoint differential equations.

5. In what fields are adjoint differential equations commonly used?

Adjoint differential equations are commonly used in the fields of engineering, physics, and mathematics. They are particularly useful in systems that involve complex dynamics, such as control systems, fluid mechanics, and quantum mechanics. They are also used in optimization problems and data assimilation methods.

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