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ISA Transactions 51 (2012) 141–145
Contents lists available at SciVerse ScienceDirect
ISA Transactions
journal homepage: www.elsevier.com/locate/isatrans
Partial stabilization-based guidance
M.H. Shafiei, T. Binazadeh∗
School of Electrical and Electronic Engineering, Shiraz University of Technology, Modares Blvd., Shiraz, Iran
a r t i c l e i n f o
Article history:
Received 5 June 2011
Received in revised form
15 August 2011
Accepted 28 August 2011
Available online 1 October 2011
Keywords:
Practical guidance scenario
Partial stability
Interception time
a b s t r a c t
A novel nonlinear missile guidance law against maneuvering targets is designed based on the principles
of partial stability. It is demonstrated that in a real approach which is adopted with actual situations,
each state of the guidance system must have a special behavior and asymptotic stability or exponential
stability of all states is not realistic. Thus, a new guidance law is developed based on the partial stability
theorem in such a way that the behaviors of states in the closed-loop system are in conformity with a
real guidance scenario that leads to collision. The performance of the proposed guidance law in terms
of interception time and control effort is compared with the sliding mode guidance law by means of
numerical simulations.
© 2011 ISA. Published by Elsevier Ltd. All rights reserved.
1. Introduction
Recently, nonlinear control theories have been used in the
design of robust guidance laws. Methods such as Lyapunov-based
nonlinear guidance laws [1–3], first-order sliding mode guidance
laws [4–8] and nonlinear H∞ guidance laws [9,10] have been
obtained from Lyapunov theorems on asymptotic stability or
exponential stability of all states. In this paper, it is shown that,
in practice, such a behavior is not realistic for all the states of a
guidance system.
It is worth noting that although the missile guidance problem
can be treated in the class of uncertain nonlinear systems, it has
a characteristic property: the missile should intercept a highly
maneuvering target within a finite interception time, sometimes
only a few seconds. In this paper, a guidance law will be designed
which guarantees the mentioned characteristic. The present work
may be classified in the category of robust guidance laws;
however, in comparison to other robust guidance laws, it follows
a completely different approach towards the missile guidance
problem. It is shown that, in a practical approach to the guidance
problem, each state has a specific behavior and there is no need
for asymptotic convergence of all the states. This is in contrast
to conventional methods in nonlinear control theory which try
to force all the states to asymptotically converge to the origin
(equilibrium point). Indeed, this paper presents a new approach in
nonlinear guidance law design. The approach is advantageous from
a practical view-point since it forces the states to behave as they
∗ Corresponding author. Fax: +98 7117353502.
E-mail addresses: shafiei@sutech.ac.ir (M.H. Shafiei), binazadeh@sutech.ac.ir
(T. Binazadeh).
need in practice and leads to classification of the state variables
of the guidance system dynamic with respect to their required
stability. The proposed guidance law is based on the principle of
partial stability, which is stability with respect to some of the state
variables.
For many engineering problems like inertial navigation sys-
tems, spacecraft stabilization via gimbaled gyroscopes or fly-
wheels, electromagnetic, adaptive stabilization, etc. [11–14], the
provision of partial stability is necessary. In the mentioned appli-
cations, while the plant may be unstable in the standard sense, it
is partially and not totally asymptotically stable. The effectiveness
of the proposed guidance law in intercepting a highly maneuver-
ing target with zero-miss-distance and finite interception time is
demonstrated analytically and through computer simulation.
2. Partial stability analysis
Partial stability is defined as the stability of a dynamical system
with respect to only some of the state variables. This approach is
essential for many engineering fields [14]. Consider a nonlinear
dynamical system:
˙x = f (x), x(t0) = x0 (1)
where x ∈ Rn
is the state vector. Let vectors x1 and x2 denote the
partitions of the state vector, respectively. Since x = (xT
1 , xT
2 )T
,
x1 ∈ Rn1 , x2 ∈ Rn2 , and n1 + n2 = n, the nonlinear system (1)
can be divided into two parts:
˙x1(t) = F1(x1(t), x2(t)), x1(t0) = x10
˙x2(t) = F2(x1(t), x2(t)), x2(t0) = x20
(2)
where x1 ∈ D ⊆ Rn1 , D is an open set including the origin, x2 ∈ Rn2
and F1 : D×Rn2 → Rn1 is such that for every x2 ∈ Rn2 , F1(0, x2) = 0
0019-0578/$ – see front matter © 2011 ISA. Published by Elsevier Ltd. All rights reserved.
doi:10.1016/j.isatra.2011.08.007
142 M.H. Shafiei, T. Binazadeh / ISA Transactions 51 (2012) 141–145
and F1(., x2) is locally Lipschitz in x1. Also, F2 : D × Rn2 → Rn2 is
such that for every x1 ∈ D, F2(x1, .) is locally Lipschitz in x2 and
Ix0
= [0, τx0
), 0 < τx0
≤ ∞ is the maximal solution existence
interval (x1(t), x2(t)) of (2) ∀t ∈ Ix0
. Under these conditions,
the existence and uniqueness of the solution is ensured. Now, the
stability of the dynamical system (2) with respect to x1 can be
defined as follows [14].
Definition 1. (i) The nonlinear system (2) is Lyapunov stable
with respect to x1 if for every ε > 0 and x20 ∈ Rn2 , there exists
δ(ε, x20) > 0 such that ‖x10‖ < δ implies ‖x1(t)‖ < ε for all
t ≥ 0.
(ii) The nonlinear system (2) is asymptotically stable with respect
to x1, if it is Lyapunov stable with respect to x1 and for every
x20 ∈ Rn2 , there exists δ = δ(x20) > 0 such that ‖x10‖ < δ
implies limt→∞ x1(t) = 0.
In order to analyze partial stability, the following theorem and its
corollary are taken from [14].
Theorem 1. Nonlinear dynamical system (2) is asymptotically stable
with respect to x1 if there exist a continuously differentiable function
V : D × Rn2 → R and class K functions α(.) and γ (.), such that
V(0, x2) = 0, x2 ∈ Rn2
(3)
α(‖x1‖) ≤ V(x1, x2), (x1, x2) ∈ D × Rn2
(4)
∂V(x1, x2)
∂x1
F1(x1, x2) +
∂V(x1, x2)
∂x2
F2(x1, x2) ≤ −γ (‖x1‖),
(x1, x2) ∈ D × Rn2
. (5)
Proof. See [14].
Corollary 1. Consider the nonlinear dynamical system (2). If there
exist a positive definite, continuously differentiable function V : D →
R and a class K function γ (.), such that
∂V(x1)
∂x1
F1(x1, x2) ≤ −γ (‖x1‖) (x1, x2) ∈ D × Rn2
(6)
then the equilibrium point of the nonlinear dynamical system (2) is
asymptotically stable with respect to x1.
Proof. See [14].
3. Application of partial stability to the missile guidance
problem
3.1. Problem formulation
In this section, a two dimensional air to air engagement is
considered. The vehicles are modeled as point masses and the
relative kinematics equation of motion between the missile and
the target is derived in the planner line of sight (LOS) coordinate
system. The center of the planner LOS coordinate system is located
on the missile. The first axis (XL) is along the LOS vector (i.e. the
vector connecting the missile to the target at each moment
and its direction is toward the target). The second axis (YL) is
perpendicular to the first one. The components of the missile and
target speed vectors (⃗vM and ⃗vT ) in the LOS coordinate system are
shown in Fig. 1.
The representation of the LOS vector in the LOS coordinate
system is as follows:
⃗r =
[
r
0
]
(7)
Fig. 1. LOS coordinate system.
where r is the relative distance between the missile and the target.
Also, the LOS vector makes an angle of θ with respect to the inertia
reference line. The LOS coordinate system rotates with respect to
the inertia reference line and ⃗ωIL – defined below – denotes the
rotation rate of the LOS-frame with respect to the inertia-frame.
The only nonzero element of this vector is perpendicular to the
plane of the LOS coordinate system:
⃗ωIL =


0
0
˙θ

 . (8)
The elements of the relative speed vector and the relative
acceleration vector in the LOS coordinate are
L
⃗vr = L
(⃗vT − ⃗vM ) =
[
vT1 − vM1
vT2 − vM2
]
=
[
vr1
vr2
]
(9)
L
⃗ar = L
(⃗aT − ⃗aM ) =
[
aT1 − aM1
aT2 − aM2
]
=
[
ar1
ar2
]
. (10)
Now, by differentiating with respect to time and use of the
Coriolis Theorem [15] the relative equations of motion in the LOS
coordinate can be obtained as follows:
L
⃗vr = L
(DI⃗r) = L
(DL⃗r) + L
⃗ωIL × L
⃗r
=

˙r
0
0

+


0
0
˙θ

 ×

r
0
0

=


˙r
r ˙θ
0

 (11)
where L
⃗vr is the relative speed vector represented in the LOS
coordinate. DI is the differential operator with respect to the inertia
coordinate and DL is the differential operator with respect to the
LOS coordinate.
Note. Since the inner product in the Coriolis Theorem is used, the
LOS vector and its derivation are shown with three elements. Of
course, the third element is always equal to zero.
Therefore, the elements of the relative speed vector in the LOS
coordinate are
[
˙r
r ˙θ
]
=
[
vT1 − vM1
vT2 − vM2
]
=
[
vr1
vr2
]
(12)
where ˙r and r ˙θ are the radial and tangential components of
the relative speed vector, respectively. Now, by differentiating
the relative speed vector, the acceleration elements in the LOS
coordinate can be obtained:
L
⃗ar = L
(DI ⃗vr ) = L
(DL⃗vr ) +L
⃗ωIL × L
⃗vr
=


¨r
r ¨θ + ˙r ˙θ
0

 +


0
0
˙θ

 ×


˙r
r ˙θ
0

 =


¨r − r ˙θ2
r ¨θ + 2˙r ˙θ
0

 . (13)
M.H. Shafiei, T. Binazadeh / ISA Transactions 51 (2012) 141–145 143
As a result, the elements of relative speed in the LOS coordinate are
[
¨r − r ˙θ2
r ¨θ + 2˙r ˙θ
=
]
=
[
aT1 − aM1
aT2 − aM2
]
=
[
ar1
ar2
]
. (14)
The above equations are defined as engagement equations. By
considering [Vr Vθ ] = [˙r r ˙θ], Eq. (14) can be rewritten in the
following way:
d
dt

r
Vr
Vθ

=


Vr
V2
θ /r
−Vr Vθ /r

 −

0 0
1 0
0 1

u +

0 0
1 0
0 1

w (15)
where x = [r, Vr , Vθ ]T
is the state vector, w = (w1, w2)T
=
(aT1, aT2)T
and u = (u1, u2)T
= (aM1, aM2)T
are the acceleration
vectors of the target and missile, respectively. Here, the accelera-
tion of the target is assumed as an external bounded disturbance
and only this bound is required in the design of the guidance law
and the accurate measurement of target acceleration during the
maneuver is not necessary. The reason for choosing r ˙θ instead of
˙θ as the third state variable is that it avoids the appearance of the
term 1/r in the control and disturbance coefficient matrix. Thus,
such a selection would make these matrices constant.
Remark 1. The initial conditions of the terminal phase are usually
in such a way that r0 > 0 and Vr0 < 0 (as assumed in the present
work). This means that the target is in front of the missile and the
missile is approaching it.
3.2. Desirable behaviors for each state
For the interception, it is sufficient that r(t) becomes zero at an
instance (r(tf ) = 0 where tf is the interception time) and there
is no need for r(t) to asymptotically converge to zero. In other
words, asymptotic convergence is not an ideal behavior for r(t).
It should be noted that asymptotic convergence behavior means
that the missile initially approaches the target very fast; however,
near the target, the relative distance reduces so slowly that the
missile touches the target in an infinite time. It is evident that such
a behavior is not a desirable behavior in missile guidance which is
intended to hit the target with a non-zero speed in a finite time. For
this purpose, it is sufficient for the relative radial speed between
the missile and the target to satisfy the following proposition.
Proposition 1. In order to intercept the target within a finite time
interval, it is sufficient to have
∃t1 ∈ [t0tf ) s.t. Vr (t) ≤ −ζ < 0 ∀t ∈ [t1tf ]. (16)
Proof. r(t) is positive and continuous. Consequently, to reach a
zero value, i.e. zero-miss-distance, within a finite time, it should
decrease from its value at t1(<tf ) down to a zero value at tf .
Inequality (16) implies r(t)−r(t1) ≤ −ζ(t −t1), which shows that
r(t) reduces within the time interval [t1 t]. Since it is desirable to
have r(tf ) = 0, thus
tf ≤
r(t1) + ζt1
ζ
. (17)
Hence, the expectation is that Vr satisfies Proposition 1. In other
words, the convergence and stability of this state are not under
consideration.
Remark 2. A common approach in relevant papers is to regulate
Vr to a negative constant c. Although this approach guarantees the
interception of the non-maneuvering target within a finite time,
it is not efficient for intercepting a highly maneuvering target in
an acceptable interception time. In such a case, to improve the
Fig. 2. Interception and non-interception regions.
performance, c should vary with time; however, to determine it,
the maneuvering model of the target should be known for the
missile, which is not always practically possible.
For the third state variable, Vθ , asymptotic convergence
behavior to zero is desirable. This results in equality of vM2 and
vT2, that is equivalent to stating that the LOS vectors remain
parallel with each other (stopping in LOS rotation). The following
discussion will clarify the reason for the acceptability of such a
behavior [16].
Consider the first equation of engagement equations (14):
¨r = r ˙θ2
+ (aT1 − aM1). (18)
Assume ˙θ is temporarily fixed and the resulting radial
acceleration components are negligible. Then the solution of this
differential equation is as follows:
r = c1eαt
+ c2e−αt
(19)
where c1 = 0.5(r0 + Vr0/α), α = |˙θ| and r0, Vr0 are the initial
conditions of engagement. Usually, these initial conditions are such
that r0 > 0 and Vr0 < 0 (refer to Remark 1). This means that the
target is in front of the missile and the missile is approaching it.
Based on these initial values, three cases might occur (in the third
quarter of the r − Vr plane).
- If c1 < 0 or r0 < −Vr0/α, then the first term in expression (19)
is negative which results in reduction of the relative distance
(r) with time. Therefore, the missile will intercept the target.
So, this area is called the ‘‘interception region’’.
- If c1 > 0 or r0 > −Vr0/α, then the relative distance increases
with time and the missile does not intercept the target. This area
is called the ‘‘non-interception region’’.
- If c1 = 0 or r0 = −Vr0/α, then there is a linear relation between
r and Vr at all moments. This line is the boundary between the
interception and non-interception regions.
These regions are shown in Fig. 2. As observed, it is obvious that
a smaller |˙θ| will result in a larger interception region. Thus, it is
desirable that ˙θ converges to zero (quickly) and stays on it. As a
result, asymptotic stability behavior is desirable for convergence of
˙θ. Also, the appropriate behavior for Vθ is the same. This is because
stopping in LOS rotation leads to a zero value for Vθ .
Therefore, the state vector may be separated into x1 = Vθ and
x2 = [r Vr ] where asymptotic stability behavior only for x1 is
desirable. By modeling the system (14) in x1 − x2 coordinates, the
following can be obtained:
˙x1 =
−Vr Vθ
r
− u2 + w2
˙x2 =


Vr
V2
θ
r
− u1 + w1

 .
(20)
It is evident that only the second component of the input vector
appears in the ˙x1-equation. Therefore, the asymptotic convergence
of Vθ may be achieved by u2. In the meantime, the appropriate
behavior of x2 could be obtained by u1.
144 M.H. Shafiei, T. Binazadeh / ISA Transactions 51 (2012) 141–145
3.3. Guidance law design
First, consider Eq. (15) where w = 0. This is equivalent to
a non-maneuvering target. Taking the Lyapunov function to be
V(x1) = 0.5x2
1 = 0.5V2
θ , the time derivative of V(x1) in the line
of the system’s trajectory is
˙V(x1) = Vθ

−Vr Vθ
r
− u2

. (21)
Take
u2 =
−Vr Vθ
r
+ NVθ . (22)
Thus, the derivative of V(x1) will satisfy the condition ˙V(x1) ≤
−γ (‖x1‖) where γ (‖x1‖) = N V2
θ . Therefore, according to Corol-
lary 1, asymptotic convergence towards zero is achieved for x1.
Also, by choosing
u1 =
V2
θ
r
− σVr σ > 0, (23)
one has ˙Vr = σVr , and consequently
Vr (t) = Vr0eσt
(24)
where Vr0 < 0 (according to Remark 1). As a result, Vr (t) ≤ Vr0
< 0. Therefore, Proposition 1 is satisfied.
Remark 3. Clearly, higher values of σ cause a shorter interception
time; however, its adjustment should be made with respect to the
physical limitations. It is worth noting that σ adjustment can also
be made in an adaptive manner and it may decrease as r decreases.
For example, it can decrease linearly as follows:
σ(t) =
[
r(t)
r0
]
σ0 +
[
1 −
r(t)
r0
]
σf (25)
where σ0 and σf denote the initial and final values of σ,
respectively.
Now, assume w ̸= 0. In this case, the target may have any ar-
bitrary maneuver with a bounded acceleration. Additional control
components, v1 and v2, may be designed in such a way as to make
the guidance law robust with respect to w. By taking
u2new (x) = u2(x) + v2(x)
= −
Vr Vθ
r
+ NVθ + v2(x) (26)
one has
˙V(x1) = −NV2
θ − Vθ (v2 − w2) (27)
where the last term, i.e., −Vθ (v2 − w2), is the effect of the control
component (v2) and disturbance term (w2). Assume |w2| ≤ η2;
therefore,
− Vθ (v2 − w2) ≤ −Vθ v2 + |Vθ ||w2|
≤ −Vθ v2 + η2|Vθ |. (28)
By choosing v2 = η2 sgn(Vθ ), one has
− Vθ (v2 − w2) ≤ −η2|Vθ | + η2|Vθ | = 0. (29)
Thus, ˙V(x1) ≤ −γ (‖x1‖) when w2 is present. Now, the addi-
tional term, v1, could be designed in such a way that the control
law, u1new (x) = u1(x) + v1(x), guarantees the specified behavior
for x2 in the presence of w1.
u1new (x) =
V2
θ
r
− σVr + v1. (30)
Assume |w1| ≤ η1, and take v1 = −η1 sgn(Vr ). Since Vr is sup-
posed to be negative, thus sgn(Vr ) = −1 and v1 = η1. By inserting
u1new in the dynamic equation (15), one has:
˙Vr = σVr − η1 + w1. (31)
Thus,
Vr (t) = Vr0eσt
+
∫ t
0
(−η1 + w1)eσ(t−τ)
dτ
≤ Vr0eσt
−
∫ t
0
η1eσ(t−τ)
dτ +
∫ t
0
η1eσ(t−τ)
dτ
≤ Vr0eσt
. (32)
Choosing −ζ = Vr0 < 0 results in Vr (t) ≤ −ζ < 0 for
t ∈ [0 tf ], for which Proposition 1 is satisfied.
Remark 4. Since discontinuous controllers suffer from chattering,
one way to alleviate this problem is to consider an approximation
of the signum function by a saturation function with a high
slope (1
ε
).
Consequently, the guidance law (33) guarantees interception of
the maneuvering target within a finite interception and zero-miss
distance:



u1new (x) =
V2
θ
r
− σVr + η1 σ, η1 > 0
u2new (x) = −
Vθ Vr
r
+ NVθ + η2sat

Vθ
ε

N, ε, η2 > 0.
(33)
3.4. Computer simulations
Numerical simulations are performed to illustrate the effective-
ness of the designed nonlinear guidance law.
The initial conditions of engagement are specified as
r(0) = 5000 m,
Vr (0) = −300 m/s,
Vθ (0) = 100/s
(34)
and the designed guidance law (33) is compared with the
sliding mode guidance law presented by the following guidance
command [8]:
u1 =
V2
θ
r
+ η1 sat

Vr − c
ε

u2 = −(N + 1)
Vr Vθ
r
+ η2 sat

Vθ
ε

.
(35)
The sliding mode guidance law has been compared with some
existing guidance laws [8]. This guidance law has obtained better
performance in terms of interception time and control effort
compared to other existing guidance laws. In this paper, it is shown
that our proposed guidance law achieves better performance
compared to the sliding mode guidance law. In both cases, a
highly maneuvering target with the following acceleration vector
is considered:
aT (t) =



200 sin
π
6
t
200 sin
π
4
t


 . (36)
The initial conditions in the inertia-frame of the missile and the
target for nonlinear simulation are given by the following.
- For the missile: xM (0) = yM (0) = 0 m.
- For the target: xT (0) = 5000 cos θ0 m, yT (0) = 5000 sin θ0 m,
vTx(0) = −200 m/s, vTy(0) = 0 m/s.
M.H. Shafiei, T. Binazadeh / ISA Transactions 51 (2012) 141–145 145
Fig. 3. (a) Trajectories of the missile and target. (b) Relative radial speed (Vr ).
Fig. 4. (a) Radial guidance command (u1). (b) Tangential guidance command (u2).
θ0 is set to be π/6. The initial values of the missile speed
components can be obtained based on the initial relative speed
components (34) and the initial values of target speeds.
The constant N is chosen as 4, while η1 and η2 are set to be 200.
Also, ε = 1, β = 0.1, σ = 0.05 and c = −800 are selected.
Fig. 3(a) shows the trajectories of the missile and the target and
Fig. 3(b) depicts the relative radial speed (Vr ). Fig. 4(a) and (b)
reflect the guidance commands.
Fig. 3(a) illustrates the collision points, C1 and C2, for the
proposed guidance law and the sliding mode guidance law,
respectively. The interception time is 7.26 s for the proposed
guidance law and 8.38 s for the sliding mode guidance law. Fig. 4(a)
demonstrates that the amount of change of radial control effort for
the proposed law is less than for the sliding mode guidance law.
Also Fig. 4(b) shows that the proposed guidance law requires less
tangential control effort than the sliding mode guidance law.
4. Conclusion
In this paper, a new approach to the missile guidance problem
was presented. It became clear that in a successful missile
guidance scenario, which leads to target interception, the desirable
behaviors of the state variables are different from each other
and asymptotic convergence behavior is not ideal for all the
state variables. Therefore, based on the partial stability theorem,
a new robust missile guidance law was developed and its
effectiveness in finite time interception of maneuvering targets
was analytically shown. Also, the proposed guidance law provided
better performance in comparison with the sliding mode guidance
law.
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[13] Vorotnikov VI. Partial stability and control: the state-of-the-art and develop-
ment prospects. Automatic Remote Control 2005;66(4):511–61.
[14] Chellaboina VS, Haddad WM. A unification between partial stability and
stability theory for time-varying systems. IEEE Control Systems Magazine
2002;22(6):66–75.
[15] Armeda MD. Analytical dynamics: theory and applications. Kluwer: Academic
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[16] Nobari JH. A novel view to engagement geometry based on proportional
navigation, Technical report, Khaje Nasir university; 2002.

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Partial stabilization based guidance

  • 1. ISA Transactions 51 (2012) 141–145 Contents lists available at SciVerse ScienceDirect ISA Transactions journal homepage: www.elsevier.com/locate/isatrans Partial stabilization-based guidance M.H. Shafiei, T. Binazadeh∗ School of Electrical and Electronic Engineering, Shiraz University of Technology, Modares Blvd., Shiraz, Iran a r t i c l e i n f o Article history: Received 5 June 2011 Received in revised form 15 August 2011 Accepted 28 August 2011 Available online 1 October 2011 Keywords: Practical guidance scenario Partial stability Interception time a b s t r a c t A novel nonlinear missile guidance law against maneuvering targets is designed based on the principles of partial stability. It is demonstrated that in a real approach which is adopted with actual situations, each state of the guidance system must have a special behavior and asymptotic stability or exponential stability of all states is not realistic. Thus, a new guidance law is developed based on the partial stability theorem in such a way that the behaviors of states in the closed-loop system are in conformity with a real guidance scenario that leads to collision. The performance of the proposed guidance law in terms of interception time and control effort is compared with the sliding mode guidance law by means of numerical simulations. © 2011 ISA. Published by Elsevier Ltd. All rights reserved. 1. Introduction Recently, nonlinear control theories have been used in the design of robust guidance laws. Methods such as Lyapunov-based nonlinear guidance laws [1–3], first-order sliding mode guidance laws [4–8] and nonlinear H∞ guidance laws [9,10] have been obtained from Lyapunov theorems on asymptotic stability or exponential stability of all states. In this paper, it is shown that, in practice, such a behavior is not realistic for all the states of a guidance system. It is worth noting that although the missile guidance problem can be treated in the class of uncertain nonlinear systems, it has a characteristic property: the missile should intercept a highly maneuvering target within a finite interception time, sometimes only a few seconds. In this paper, a guidance law will be designed which guarantees the mentioned characteristic. The present work may be classified in the category of robust guidance laws; however, in comparison to other robust guidance laws, it follows a completely different approach towards the missile guidance problem. It is shown that, in a practical approach to the guidance problem, each state has a specific behavior and there is no need for asymptotic convergence of all the states. This is in contrast to conventional methods in nonlinear control theory which try to force all the states to asymptotically converge to the origin (equilibrium point). Indeed, this paper presents a new approach in nonlinear guidance law design. The approach is advantageous from a practical view-point since it forces the states to behave as they ∗ Corresponding author. Fax: +98 7117353502. E-mail addresses: shafiei@sutech.ac.ir (M.H. Shafiei), binazadeh@sutech.ac.ir (T. Binazadeh). need in practice and leads to classification of the state variables of the guidance system dynamic with respect to their required stability. The proposed guidance law is based on the principle of partial stability, which is stability with respect to some of the state variables. For many engineering problems like inertial navigation sys- tems, spacecraft stabilization via gimbaled gyroscopes or fly- wheels, electromagnetic, adaptive stabilization, etc. [11–14], the provision of partial stability is necessary. In the mentioned appli- cations, while the plant may be unstable in the standard sense, it is partially and not totally asymptotically stable. The effectiveness of the proposed guidance law in intercepting a highly maneuver- ing target with zero-miss-distance and finite interception time is demonstrated analytically and through computer simulation. 2. Partial stability analysis Partial stability is defined as the stability of a dynamical system with respect to only some of the state variables. This approach is essential for many engineering fields [14]. Consider a nonlinear dynamical system: ˙x = f (x), x(t0) = x0 (1) where x ∈ Rn is the state vector. Let vectors x1 and x2 denote the partitions of the state vector, respectively. Since x = (xT 1 , xT 2 )T , x1 ∈ Rn1 , x2 ∈ Rn2 , and n1 + n2 = n, the nonlinear system (1) can be divided into two parts: ˙x1(t) = F1(x1(t), x2(t)), x1(t0) = x10 ˙x2(t) = F2(x1(t), x2(t)), x2(t0) = x20 (2) where x1 ∈ D ⊆ Rn1 , D is an open set including the origin, x2 ∈ Rn2 and F1 : D×Rn2 → Rn1 is such that for every x2 ∈ Rn2 , F1(0, x2) = 0 0019-0578/$ – see front matter © 2011 ISA. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.isatra.2011.08.007
  • 2. 142 M.H. Shafiei, T. Binazadeh / ISA Transactions 51 (2012) 141–145 and F1(., x2) is locally Lipschitz in x1. Also, F2 : D × Rn2 → Rn2 is such that for every x1 ∈ D, F2(x1, .) is locally Lipschitz in x2 and Ix0 = [0, τx0 ), 0 < τx0 ≤ ∞ is the maximal solution existence interval (x1(t), x2(t)) of (2) ∀t ∈ Ix0 . Under these conditions, the existence and uniqueness of the solution is ensured. Now, the stability of the dynamical system (2) with respect to x1 can be defined as follows [14]. Definition 1. (i) The nonlinear system (2) is Lyapunov stable with respect to x1 if for every ε > 0 and x20 ∈ Rn2 , there exists δ(ε, x20) > 0 such that ‖x10‖ < δ implies ‖x1(t)‖ < ε for all t ≥ 0. (ii) The nonlinear system (2) is asymptotically stable with respect to x1, if it is Lyapunov stable with respect to x1 and for every x20 ∈ Rn2 , there exists δ = δ(x20) > 0 such that ‖x10‖ < δ implies limt→∞ x1(t) = 0. In order to analyze partial stability, the following theorem and its corollary are taken from [14]. Theorem 1. Nonlinear dynamical system (2) is asymptotically stable with respect to x1 if there exist a continuously differentiable function V : D × Rn2 → R and class K functions α(.) and γ (.), such that V(0, x2) = 0, x2 ∈ Rn2 (3) α(‖x1‖) ≤ V(x1, x2), (x1, x2) ∈ D × Rn2 (4) ∂V(x1, x2) ∂x1 F1(x1, x2) + ∂V(x1, x2) ∂x2 F2(x1, x2) ≤ −γ (‖x1‖), (x1, x2) ∈ D × Rn2 . (5) Proof. See [14]. Corollary 1. Consider the nonlinear dynamical system (2). If there exist a positive definite, continuously differentiable function V : D → R and a class K function γ (.), such that ∂V(x1) ∂x1 F1(x1, x2) ≤ −γ (‖x1‖) (x1, x2) ∈ D × Rn2 (6) then the equilibrium point of the nonlinear dynamical system (2) is asymptotically stable with respect to x1. Proof. See [14]. 3. Application of partial stability to the missile guidance problem 3.1. Problem formulation In this section, a two dimensional air to air engagement is considered. The vehicles are modeled as point masses and the relative kinematics equation of motion between the missile and the target is derived in the planner line of sight (LOS) coordinate system. The center of the planner LOS coordinate system is located on the missile. The first axis (XL) is along the LOS vector (i.e. the vector connecting the missile to the target at each moment and its direction is toward the target). The second axis (YL) is perpendicular to the first one. The components of the missile and target speed vectors (⃗vM and ⃗vT ) in the LOS coordinate system are shown in Fig. 1. The representation of the LOS vector in the LOS coordinate system is as follows: ⃗r = [ r 0 ] (7) Fig. 1. LOS coordinate system. where r is the relative distance between the missile and the target. Also, the LOS vector makes an angle of θ with respect to the inertia reference line. The LOS coordinate system rotates with respect to the inertia reference line and ⃗ωIL – defined below – denotes the rotation rate of the LOS-frame with respect to the inertia-frame. The only nonzero element of this vector is perpendicular to the plane of the LOS coordinate system: ⃗ωIL =   0 0 ˙θ   . (8) The elements of the relative speed vector and the relative acceleration vector in the LOS coordinate are L ⃗vr = L (⃗vT − ⃗vM ) = [ vT1 − vM1 vT2 − vM2 ] = [ vr1 vr2 ] (9) L ⃗ar = L (⃗aT − ⃗aM ) = [ aT1 − aM1 aT2 − aM2 ] = [ ar1 ar2 ] . (10) Now, by differentiating with respect to time and use of the Coriolis Theorem [15] the relative equations of motion in the LOS coordinate can be obtained as follows: L ⃗vr = L (DI⃗r) = L (DL⃗r) + L ⃗ωIL × L ⃗r =  ˙r 0 0  +   0 0 ˙θ   ×  r 0 0  =   ˙r r ˙θ 0   (11) where L ⃗vr is the relative speed vector represented in the LOS coordinate. DI is the differential operator with respect to the inertia coordinate and DL is the differential operator with respect to the LOS coordinate. Note. Since the inner product in the Coriolis Theorem is used, the LOS vector and its derivation are shown with three elements. Of course, the third element is always equal to zero. Therefore, the elements of the relative speed vector in the LOS coordinate are [ ˙r r ˙θ ] = [ vT1 − vM1 vT2 − vM2 ] = [ vr1 vr2 ] (12) where ˙r and r ˙θ are the radial and tangential components of the relative speed vector, respectively. Now, by differentiating the relative speed vector, the acceleration elements in the LOS coordinate can be obtained: L ⃗ar = L (DI ⃗vr ) = L (DL⃗vr ) +L ⃗ωIL × L ⃗vr =   ¨r r ¨θ + ˙r ˙θ 0   +   0 0 ˙θ   ×   ˙r r ˙θ 0   =   ¨r − r ˙θ2 r ¨θ + 2˙r ˙θ 0   . (13)
  • 3. M.H. Shafiei, T. Binazadeh / ISA Transactions 51 (2012) 141–145 143 As a result, the elements of relative speed in the LOS coordinate are [ ¨r − r ˙θ2 r ¨θ + 2˙r ˙θ = ] = [ aT1 − aM1 aT2 − aM2 ] = [ ar1 ar2 ] . (14) The above equations are defined as engagement equations. By considering [Vr Vθ ] = [˙r r ˙θ], Eq. (14) can be rewritten in the following way: d dt  r Vr Vθ  =   Vr V2 θ /r −Vr Vθ /r   −  0 0 1 0 0 1  u +  0 0 1 0 0 1  w (15) where x = [r, Vr , Vθ ]T is the state vector, w = (w1, w2)T = (aT1, aT2)T and u = (u1, u2)T = (aM1, aM2)T are the acceleration vectors of the target and missile, respectively. Here, the accelera- tion of the target is assumed as an external bounded disturbance and only this bound is required in the design of the guidance law and the accurate measurement of target acceleration during the maneuver is not necessary. The reason for choosing r ˙θ instead of ˙θ as the third state variable is that it avoids the appearance of the term 1/r in the control and disturbance coefficient matrix. Thus, such a selection would make these matrices constant. Remark 1. The initial conditions of the terminal phase are usually in such a way that r0 > 0 and Vr0 < 0 (as assumed in the present work). This means that the target is in front of the missile and the missile is approaching it. 3.2. Desirable behaviors for each state For the interception, it is sufficient that r(t) becomes zero at an instance (r(tf ) = 0 where tf is the interception time) and there is no need for r(t) to asymptotically converge to zero. In other words, asymptotic convergence is not an ideal behavior for r(t). It should be noted that asymptotic convergence behavior means that the missile initially approaches the target very fast; however, near the target, the relative distance reduces so slowly that the missile touches the target in an infinite time. It is evident that such a behavior is not a desirable behavior in missile guidance which is intended to hit the target with a non-zero speed in a finite time. For this purpose, it is sufficient for the relative radial speed between the missile and the target to satisfy the following proposition. Proposition 1. In order to intercept the target within a finite time interval, it is sufficient to have ∃t1 ∈ [t0tf ) s.t. Vr (t) ≤ −ζ < 0 ∀t ∈ [t1tf ]. (16) Proof. r(t) is positive and continuous. Consequently, to reach a zero value, i.e. zero-miss-distance, within a finite time, it should decrease from its value at t1(<tf ) down to a zero value at tf . Inequality (16) implies r(t)−r(t1) ≤ −ζ(t −t1), which shows that r(t) reduces within the time interval [t1 t]. Since it is desirable to have r(tf ) = 0, thus tf ≤ r(t1) + ζt1 ζ . (17) Hence, the expectation is that Vr satisfies Proposition 1. In other words, the convergence and stability of this state are not under consideration. Remark 2. A common approach in relevant papers is to regulate Vr to a negative constant c. Although this approach guarantees the interception of the non-maneuvering target within a finite time, it is not efficient for intercepting a highly maneuvering target in an acceptable interception time. In such a case, to improve the Fig. 2. Interception and non-interception regions. performance, c should vary with time; however, to determine it, the maneuvering model of the target should be known for the missile, which is not always practically possible. For the third state variable, Vθ , asymptotic convergence behavior to zero is desirable. This results in equality of vM2 and vT2, that is equivalent to stating that the LOS vectors remain parallel with each other (stopping in LOS rotation). The following discussion will clarify the reason for the acceptability of such a behavior [16]. Consider the first equation of engagement equations (14): ¨r = r ˙θ2 + (aT1 − aM1). (18) Assume ˙θ is temporarily fixed and the resulting radial acceleration components are negligible. Then the solution of this differential equation is as follows: r = c1eαt + c2e−αt (19) where c1 = 0.5(r0 + Vr0/α), α = |˙θ| and r0, Vr0 are the initial conditions of engagement. Usually, these initial conditions are such that r0 > 0 and Vr0 < 0 (refer to Remark 1). This means that the target is in front of the missile and the missile is approaching it. Based on these initial values, three cases might occur (in the third quarter of the r − Vr plane). - If c1 < 0 or r0 < −Vr0/α, then the first term in expression (19) is negative which results in reduction of the relative distance (r) with time. Therefore, the missile will intercept the target. So, this area is called the ‘‘interception region’’. - If c1 > 0 or r0 > −Vr0/α, then the relative distance increases with time and the missile does not intercept the target. This area is called the ‘‘non-interception region’’. - If c1 = 0 or r0 = −Vr0/α, then there is a linear relation between r and Vr at all moments. This line is the boundary between the interception and non-interception regions. These regions are shown in Fig. 2. As observed, it is obvious that a smaller |˙θ| will result in a larger interception region. Thus, it is desirable that ˙θ converges to zero (quickly) and stays on it. As a result, asymptotic stability behavior is desirable for convergence of ˙θ. Also, the appropriate behavior for Vθ is the same. This is because stopping in LOS rotation leads to a zero value for Vθ . Therefore, the state vector may be separated into x1 = Vθ and x2 = [r Vr ] where asymptotic stability behavior only for x1 is desirable. By modeling the system (14) in x1 − x2 coordinates, the following can be obtained: ˙x1 = −Vr Vθ r − u2 + w2 ˙x2 =   Vr V2 θ r − u1 + w1   . (20) It is evident that only the second component of the input vector appears in the ˙x1-equation. Therefore, the asymptotic convergence of Vθ may be achieved by u2. In the meantime, the appropriate behavior of x2 could be obtained by u1.
  • 4. 144 M.H. Shafiei, T. Binazadeh / ISA Transactions 51 (2012) 141–145 3.3. Guidance law design First, consider Eq. (15) where w = 0. This is equivalent to a non-maneuvering target. Taking the Lyapunov function to be V(x1) = 0.5x2 1 = 0.5V2 θ , the time derivative of V(x1) in the line of the system’s trajectory is ˙V(x1) = Vθ  −Vr Vθ r − u2  . (21) Take u2 = −Vr Vθ r + NVθ . (22) Thus, the derivative of V(x1) will satisfy the condition ˙V(x1) ≤ −γ (‖x1‖) where γ (‖x1‖) = N V2 θ . Therefore, according to Corol- lary 1, asymptotic convergence towards zero is achieved for x1. Also, by choosing u1 = V2 θ r − σVr σ > 0, (23) one has ˙Vr = σVr , and consequently Vr (t) = Vr0eσt (24) where Vr0 < 0 (according to Remark 1). As a result, Vr (t) ≤ Vr0 < 0. Therefore, Proposition 1 is satisfied. Remark 3. Clearly, higher values of σ cause a shorter interception time; however, its adjustment should be made with respect to the physical limitations. It is worth noting that σ adjustment can also be made in an adaptive manner and it may decrease as r decreases. For example, it can decrease linearly as follows: σ(t) = [ r(t) r0 ] σ0 + [ 1 − r(t) r0 ] σf (25) where σ0 and σf denote the initial and final values of σ, respectively. Now, assume w ̸= 0. In this case, the target may have any ar- bitrary maneuver with a bounded acceleration. Additional control components, v1 and v2, may be designed in such a way as to make the guidance law robust with respect to w. By taking u2new (x) = u2(x) + v2(x) = − Vr Vθ r + NVθ + v2(x) (26) one has ˙V(x1) = −NV2 θ − Vθ (v2 − w2) (27) where the last term, i.e., −Vθ (v2 − w2), is the effect of the control component (v2) and disturbance term (w2). Assume |w2| ≤ η2; therefore, − Vθ (v2 − w2) ≤ −Vθ v2 + |Vθ ||w2| ≤ −Vθ v2 + η2|Vθ |. (28) By choosing v2 = η2 sgn(Vθ ), one has − Vθ (v2 − w2) ≤ −η2|Vθ | + η2|Vθ | = 0. (29) Thus, ˙V(x1) ≤ −γ (‖x1‖) when w2 is present. Now, the addi- tional term, v1, could be designed in such a way that the control law, u1new (x) = u1(x) + v1(x), guarantees the specified behavior for x2 in the presence of w1. u1new (x) = V2 θ r − σVr + v1. (30) Assume |w1| ≤ η1, and take v1 = −η1 sgn(Vr ). Since Vr is sup- posed to be negative, thus sgn(Vr ) = −1 and v1 = η1. By inserting u1new in the dynamic equation (15), one has: ˙Vr = σVr − η1 + w1. (31) Thus, Vr (t) = Vr0eσt + ∫ t 0 (−η1 + w1)eσ(t−τ) dτ ≤ Vr0eσt − ∫ t 0 η1eσ(t−τ) dτ + ∫ t 0 η1eσ(t−τ) dτ ≤ Vr0eσt . (32) Choosing −ζ = Vr0 < 0 results in Vr (t) ≤ −ζ < 0 for t ∈ [0 tf ], for which Proposition 1 is satisfied. Remark 4. Since discontinuous controllers suffer from chattering, one way to alleviate this problem is to consider an approximation of the signum function by a saturation function with a high slope (1 ε ). Consequently, the guidance law (33) guarantees interception of the maneuvering target within a finite interception and zero-miss distance:    u1new (x) = V2 θ r − σVr + η1 σ, η1 > 0 u2new (x) = − Vθ Vr r + NVθ + η2sat  Vθ ε  N, ε, η2 > 0. (33) 3.4. Computer simulations Numerical simulations are performed to illustrate the effective- ness of the designed nonlinear guidance law. The initial conditions of engagement are specified as r(0) = 5000 m, Vr (0) = −300 m/s, Vθ (0) = 100/s (34) and the designed guidance law (33) is compared with the sliding mode guidance law presented by the following guidance command [8]: u1 = V2 θ r + η1 sat  Vr − c ε  u2 = −(N + 1) Vr Vθ r + η2 sat  Vθ ε  . (35) The sliding mode guidance law has been compared with some existing guidance laws [8]. This guidance law has obtained better performance in terms of interception time and control effort compared to other existing guidance laws. In this paper, it is shown that our proposed guidance law achieves better performance compared to the sliding mode guidance law. In both cases, a highly maneuvering target with the following acceleration vector is considered: aT (t) =    200 sin π 6 t 200 sin π 4 t    . (36) The initial conditions in the inertia-frame of the missile and the target for nonlinear simulation are given by the following. - For the missile: xM (0) = yM (0) = 0 m. - For the target: xT (0) = 5000 cos θ0 m, yT (0) = 5000 sin θ0 m, vTx(0) = −200 m/s, vTy(0) = 0 m/s.
  • 5. M.H. Shafiei, T. Binazadeh / ISA Transactions 51 (2012) 141–145 145 Fig. 3. (a) Trajectories of the missile and target. (b) Relative radial speed (Vr ). Fig. 4. (a) Radial guidance command (u1). (b) Tangential guidance command (u2). θ0 is set to be π/6. The initial values of the missile speed components can be obtained based on the initial relative speed components (34) and the initial values of target speeds. The constant N is chosen as 4, while η1 and η2 are set to be 200. Also, ε = 1, β = 0.1, σ = 0.05 and c = −800 are selected. Fig. 3(a) shows the trajectories of the missile and the target and Fig. 3(b) depicts the relative radial speed (Vr ). Fig. 4(a) and (b) reflect the guidance commands. Fig. 3(a) illustrates the collision points, C1 and C2, for the proposed guidance law and the sliding mode guidance law, respectively. The interception time is 7.26 s for the proposed guidance law and 8.38 s for the sliding mode guidance law. Fig. 4(a) demonstrates that the amount of change of radial control effort for the proposed law is less than for the sliding mode guidance law. Also Fig. 4(b) shows that the proposed guidance law requires less tangential control effort than the sliding mode guidance law. 4. Conclusion In this paper, a new approach to the missile guidance problem was presented. It became clear that in a successful missile guidance scenario, which leads to target interception, the desirable behaviors of the state variables are different from each other and asymptotic convergence behavior is not ideal for all the state variables. Therefore, based on the partial stability theorem, a new robust missile guidance law was developed and its effectiveness in finite time interception of maneuvering targets was analytically shown. Also, the proposed guidance law provided better performance in comparison with the sliding mode guidance law. References [1] Lechevin N, Rabbath CA. Lyapunov-based nonlinear Missile guidance. Journal of Guidance, Control, and Dynamics 2004;27(6):1096–102. [2] Ryoo CK, Kim YH, Tahk MJ, Choi K. A Missile guidance law based on Sontag’s formula to intercept maneuvering targets. International Journal of Control, Automation, and Systems 2007;5(4):397–409. [3] Shieh CS. Nonlinear rule-based controller for missile terminal guidance. IEE Proceedings-Control Theory Application 2004;150(1):45–8. [4] Zhou D, Mu C, Xu W. Adapt sliding-mode guidance of a homing Missile. Journal of Guidance, Control, and Dynamics 1999;22(4):589–94. [5] Liaw DC, Liang YW, Cheng CC. Nonlinear control for missile terminal guidance. Journal of Dynamic Systems, Measurement, and Control 2000;122(663): 663–8. [6] Brierly SD, Longchamp R. Application of sliding mode control to air–air interception problem. IEEE Transactions on Aerospace and Electronic Systems 1990;26(2):306–25. [7] Idan M, Shima T, Golan OM. Integrated sliding mode autopilot-guidance for dual control missiles. in: AIAA guidance, navigation, and control conference and exhibit. 2005. [8] Moon J, Kim K, Kim Y. Design of Missile law via variable structure control. Journal of Guidance, Control and Dynamics 2001;24(4):659–64. [9] Tang CD, Chen HY. Nonlinear H∞ Robust guidance law for homing Missiles. Journal of Guidance, Control and Dynamics 1998;21(6):882–90. [10] Chen BS, Chen YY, Lin CL. Nonlinear fuzzy H∞ guidance law with saturation of actuators against maneuvering targets. IEEE Transactions on Control System Technology 2002;10(6):769–79. [11] Vorotnikov VI. Partial stability and control. Boston: Birkhauser; 1998. [12] Hu W, Wang J, Li X. An approach of partial control design for system control and synchronization. Chaos, Solitons & Fractals 2009;39(3):1410–7. [13] Vorotnikov VI. Partial stability and control: the state-of-the-art and develop- ment prospects. Automatic Remote Control 2005;66(4):511–61. [14] Chellaboina VS, Haddad WM. A unification between partial stability and stability theory for time-varying systems. IEEE Control Systems Magazine 2002;22(6):66–75. [15] Armeda MD. Analytical dynamics: theory and applications. Kluwer: Academic Plenum Publishers; 2005. [16] Nobari JH. A novel view to engagement geometry based on proportional navigation, Technical report, Khaje Nasir university; 2002.