We firstly recall from Chapter 1 the basic form of our controlled ODE:

Here x⁰ ∈ Rⁿ, f : Rⁿ ×A → Rⁿ, α : [0,∞) → A is the control, and x : [0,∞) → Rⁿ is the response of the system.

This chapter addresses the following basic

CONTROLLABILITY QUESTION: Given the initial point x0 and a “target”  set S ⊂ Rⁿ, does there exist a control steering the system to S in finite time?

For the time being we will therefore not introduce any payoff criterion that would characterize an “optimal” control, but instead will focus on the question as to whether or not there exist controls that steer the system to a given goal. In this chapter we will mostly consider the problem of driving the system to the origin S = {0}.

DEFINITION. We define the reachable set for time t to be C(t) = set of initial points x0 for which there exists a control such that x(t) = 0,  and the overall reachable set

C = set of initial points x0 for which there exists a control such that x(t) = 0 for some finite time t.

Note that

Hereafter, let M^n×m denote the set of all n × m matrices. We assume for the rest of this and the next chapter that our ODE is linear in both the state x(.) and the control α(.), and consequently has the form

where M ∈ M^n×n and N ∈ M^n×m. We assume the set A of control parameters is a cube in R^m:

                       A = [−1, 1]

                                 m = {a ∈ R^m | |a_i| ≤ 1, i = 1, . . . ,m}.

References

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مواضيع ذات صلة

DYNAMIC PROGRAMMING-DYNAMIC PROGRAMMING AND THE PONTRYAGIN MAXIMUM PRINCIPLE

DYNAMIC PROGRAMMING-EXAMPLES

DERIVATION OF BELLMAN,S PDE-DYNAMIC PROGRAMMING

THE PONTRYAGIN MAXIMUM PRINCIPLE-MORE APPLICATIONS

THE PONTRYAGIN MAXIMUM PRINCIPLE-MAXIMUM PRINCIPLE WITH STATE CONSTRAINTS

THE PONTRYAGIN MAXIMUM PRINCIPLE-MORE APPLICATIONS

THE PONTRYAGIN MAXIMUM PRINCIPLE-MAXIMUMPRINCIPLEWITH TRANSVERSALITY CONDITIONS

THE PONTRYAGIN MAXIMUM PRINCIPLE-APPLICATIONS AND EXAMPLES

THE PONTRYAGIN MAXIMUM PRINCIPLE-STATEMENT OF PONTRYAGIN MAXIMUM PRINCIPLE

THE PONTRYAGIN MAXIMUM PRINCIPLE-REVIEW OF LAGRANGE MULTIPLIERS.

THE PONTRYAGIN MAXIMUM PRINCIPLE-CALCULUS OF VARIATIONS, HAMILTONIAN DYNAMICS

LINEAR TIME-OPTIMAL CONTROL-EXAMPLES