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Thesis - Leigh Moody.pdf - Bad Request - Cranfield University

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Chapter 6 / Missile Guidance<br />

_ _<br />

(1996) for being too restrictive in the allowable initial conditions to ensure<br />

capture, giving this as the reason for reduced capture regions rather than<br />

target dynamics.<br />

6.5.1.5 Optimal PN<br />

The development of guidance laws using classical methods has gradually<br />

been replaced by optimal techniques with Performance Indices (PI) able to<br />

cope with non-linear stochastic systems, Vergez [V.1] . Originally, such laws<br />

were derived for linear systems subject to Gaussian disturbances and<br />

quadratic PI. The resulting Linear Quadratic Regulator (LQR) problem is<br />

one of finding a control vector (U) that minimises the PI denoted by J(U):<br />

X<br />

T<br />

( t ) : = [ A ] ⋅ X ( t ) + [ B ] U ( t )<br />

X& ⋅<br />

tF<br />

J<br />

6-12<br />

( U )<br />

Equation 6.5-1<br />

( ) dt<br />

T<br />

T<br />

T<br />

( t ) ⋅ [ G ] ⋅ X ( t ) + X ⋅ [ W ] ⋅ X + U ( t ) ⋅ [ R ] ⋅ U ( t )<br />

F<br />

F<br />

∫<br />

t<br />

: =<br />

Equation 6.5-2<br />

The PI comprises terms defined by the system state (X) and controls (U)<br />

during flight, and at the impact time (tF). The weighting between them<br />

determined by [G], [W] and [R]. The steady-state solution is obtained from<br />

the Riccati equation:<br />

P&<br />

+ P<br />

T<br />

⋅<br />

T<br />

−1<br />

T T<br />

[ A ] + [ A ] ⋅ P − P ⋅ [ B ] ⋅ R ⋅ [ B ] ⋅ P + [ W ] : = 0<br />

Resulting in the optimal control sequence,<br />

(<br />

U ⋅<br />

−1<br />

T<br />

T<br />

( t ) : = −[<br />

R ] ⋅ [ B ] ⋅ P ( t ) X<br />

Equation 6.5-3<br />

Equation 6.5-4<br />

Thus the constrained Bolza problem from variational calculus can be solved<br />

explicitly to obtain closed loop optimal guidance laws, Rusnack [R.1-4] . The<br />

solution involves the state at the integration limits and as such is referred to<br />

as a Two Point Boundary Value Problem (TPBVP). The Bolza form is a<br />

combination of the Mayer problem, dealing with the terminal cost, and the<br />

Lagrangian problem dealing with the cumulative effect of the state and<br />

controls. Mayer problems generate control sequences that bring the state of<br />

the plant to a desired condition at impact, the optimal control sequence<br />

reducing the PI to zero. Whilst ideal for miss distance, impact speed and<br />

aspect, and minimal flight times, they disregard the “cost” associated with

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