# Nonsingular Continuous Finite-Time Convergent Guidance Law with Impact Angle Constraints

Authors: Luyao Zang; Defu Lin; Yi Ji
Journal: International Journal of Aerospace Engineering
 (2019)

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## Abstract

This paper documents a novel nonsingular continuous guidance which can drive the line-of-sight (LOS) angular rate to converge to zero in finite time in the presence of impact angle constraints. More specifically, based on the second-order sliding mode control (SMC) theory, a second-order observer (2-OB) is presented to estimate the unknown target maneuvers, while a super twisting algorithm- (STA-) based guidance law is presented to restrict the LOS angle and angular rate. Compared with other terminal sliding mode guidance laws, the proposed guidance law absorbs the merits of the conventional linear sliding mode (LSM) and terminal sliding mode (TSM) and uses switching technique to avoid singularity. In order to verify the stability of the proposed guidance law, a finite-time bounded (FTB) function is invited to prove the boundedness of the proposed observer-controller system and a Lyapunov approach is presented to prove the finite-time convergence (FTC) of the proposed sliding system. Rigorous theoretical analysis and numerical simulations demonstrate the mentioned properties.


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## Body

## 1. Introduction

Facing the modern battleground, zero miss distance is not the only operational effect index of accurately guided weapon guidance [1]. The complex combat circumstance requires some new properties, such as energy optimization, interference resistance, and impact angle constraints. Among these requirements, impact angle constraints are one of the prerequisites for some real cases. For example, for a missile against a tank, it is easy to pierce the top rather than the armored body; this process requires that the missile intercepts the tank within a limited impact angle range that can be realized by using a reasonable guidance law design.Because of their effectiveness, ease of implementation, and successful history of application, the well-known proportional navigation guidance (PNG) law [2–5] and its variants have been widely used in engineering practice in the last few decades. The key point of PNG is to drive the LOS angular rate to zero to guide the missile to intercept the target with zero miss distance. However, because of the terrible disturbance resulting from target maneuvers, environment noise, and measurement error, PNG cannot provide the qualified performance in some extreme cases. For example, for missiles with maneuvering targets, such as interceptors or air-to-air missiles, the LOS angular rate usually varies with the target maneuvers; this variation always results in perturbations that PNG or argument PNG cannot cope with. Hence, it is necessary to design a novel robust guidance law to resist this perturbation.With the development of the modern control theory in recent years, many scholars proposed many advanced guidance laws for intercepting maneuvering targets. To cite some typical works, to attenuate the effect of bounded uncertain and unknown interference, Yang and Chen [6] proposed a robust H-infinity guidance law by regarding unpredictable target maneuvers as bounded unknowns. Based on the results of their research, Liu and Shen [7] presented a novel three-dimensional spherical H-infinity guidance law that takes missile acceleration constraints into account. By formulating interception as a nonlinear perturbation attenuation H-infinity problem, Yang and Chen [8] presented a novel robust guidance law. Zhou et al. [9] presented a L2 gain performance guidance law with the aid of a Lyapunov-like approach. In the work of Yan and Ji [10], a novel input-to-state stability-based guidance (ISSG) law was proposed to limit bounded target maneuvers and estimate the bounded LOS angular rate. In addition to the mentioned guidance laws and their variants, SMC-based guidance laws are alternatives to the most popular guidance laws because of their inherent strong robustness and FTC properties.Second-order SMC is a useful method to allow guided missiles to intercept maneuvering targets with the desired impact angles. Because of its robustness, global convergence, and order reduction, the sliding mode controller has drawn great attention from research communities and has been used in a variety of applications in various fields, such as missile guidance, autopilots of unmanned air vehicles (UAV), robotic manipulator control, and microelectromechanical system (MEMS) gyroscopes [11–14]. Based on the SMC theory, many advanced guidance laws were coined for maneuvering targets. For example, by using the SMC technique, Zhou et al. [15] proposed a novel FTC guidance law to guide the LOS angular rate to converge to zero or within a small neighborhood of zero in finite time. Facing planar interception, Moon et al. [16] provided an adaptive sliding mode guidance approach based on the reaching law, in which the key point is that the convergent rate should increase in proportion to the decrease in the distance between the missile and the target. By using the so-called inertial delay control (IDC) technique to estimate the target acceleration, Phadke and Talole [17] proposed an SMC-based PN guidance law that requires no knowledge of the bounds of the target acceleration. Kumar et al. [18] proposed a planar nonsingular terminal sliding mode guidance law in the presence of impact angle constraints; however, they did not consider the FTC property.For a LOS angle constrained maneuvering target interception, some challenges should be taken into account. First, the knowledge of a LOS angle is difficult to be obtained, especially when the target is moving with a large velocity and a large acceleration. Next, in real practice, the properties of the actuator, such as the response rate and efficiency margin, are another two important factors which also should be taken into consideration. In addition, some perturbations such as measurement error and environmental noise may result in performance degradation. Considering these problems, this paper discusses a new nonsingular continuous impact-angle-constraint SMC guidance law that forces the system state to converge to a sliding manifold in finite time as well as drives the sliding manifold to converge to zero in finite time. By using a switchable design of the sliding manifold, this control approach avoids the singularity that a conventional TSM can encounter. Furthermore, this guidance law utilizes the STA algorithm to reduce the chattering phenomenon. Moreover, a 2-OB which can track the unknown trajectory is employed to estimate the target maneuvers. Combining with the proposed observer and guidance algorithm, the LOS angle error (the difference between the desired LOS angle and the real LOS angle) and LOS angular rate can converge to zero in finite time.The rest of this paper is organized as follows: the planar and spherical mathematical model of the engagement phase is provided, and the guidance strategy is discussed in Section2; the 2-OB and the finite-time convergent guidance approach is proposed in Section 3; some simulation results are given and discussed in Section 4; a brief conclusion of this paper is given in Section 5; some proofs of the proposed propositions are given in Appendices A, B, and III.


## 2. Problem Formulation

### 2.1. Planar Mathematical Model of the Engagement Phase

Throughout the paper, the research object is assumed to satisfy the following hypothesizes: (i) the mass of the missile is in uniform distribution, (ii) the no roll or roll rate is small enough, and (iii) the mechanical properties of the missile are similar in every direction perpendicular to the roll axis. As a result, the missile can be regarded as a point mass. To simplify the problem, the relationship between the missile and the target during the engagement phase can be taken into account as a planar interception, which is illustrated in Figure1.Figure 1
The planar model of the relationship between the missile and the target.From Figure1, one can conclude that
(1)ṙ=VTcosγT−λ−VMcosγM−λ,(2)λ̇=VTsinγT−λ−VMcosγM−λr,(3)γ̇M=aMVM,(4)γ̇T=aTVT,where M denotes the missile and T denotes the target; VT and VM denote the velocities of the target and the missile, respectively; aT and aM denote the accelerations of the target and the missile, respectively; r and ṙ denote the distance and its derivative, respectively, between the missile and the target; λ and λ̇ denote the LOS angle and the LOS angular rate, respectively; γM and γ̇M denote the heading angle and the heading angular rate of the missile, respectively; γT and γ̇T denote the heading angle and the heading angular rate of the target, respectively.Taking the derivative of equation (1) and equation (2) with respect to time yields
(5)r¨=rλ̇2+aTr−aMr,(6)λ¨=−2ṙλ̇r+aTλr−aMλr.Here,aTr=aTsinλ−γT and aMr=aMsinλ−γM denote accelerations following the LOS direction of the target and the missile, respectively. aTλ=aTcosλ−γT and aMλ=aMcosλ−γM denote accelerations perpendicular to the LOS direction of the target and the missile, respectively. This completes the planar mathematical model.Remark 1.
For a missile controlled by active forces, equation (5) and equation (6) must be considered simultaneously during the process of guidance law design. However, for a missile only controlled by aerodynamic forces, the velocity in the LOS direction can be regard as constant. Hence, using only equation (6) to design the guidance law is adequate.


### 2.2. Strategy of Interception

According to the zeroing LOS angular rate principle, assuming that the LOS angular rate will converge to zero when collision occurs, from equation (2), one can infer that
(7)VTsinγTf−λf=VMsinγMf−λf,where the subscript f denotes the values of the relevant parameters at terminal time.Denote impact angleθimp as the following equation:
(8)θimp=γTf−γMf.Substituting equation (8) into equation (7) yields
(9)VTsinγTf−λf−VMsinγTf−θimp−λf=0.By assuming thatVT<VM, solving equation (9) yields
(10)λf=γTf−tan−1sinθimpcosθimp−VT/VM.From equation (10), one can conclude that, for any given impact angle θimp, there must exist one and one only relevant LOS angle. In other words, the problem of impact angle constraints can be transformed as the tracking LOS angle problem. We can design a Lyapunov approach to drive the LOS angle λ to converge to the desired LOS angle λd and the LOS angular rate λ̇ to converge to zero in finite time to solve this problem.


### 2.3. Some Assumptions and Lemmas

The following assumptions and lemmas are used throughout this paper.Assumption 1.
There must exist a minimum distancermin between the missile and the target. For any given r, the following is required: r≥rmin.Remark 3.
Because of the length of the missile and the length of the target from the shells to the point masses, Assumption1 is reasonable.Assumption 2.
Because of the physical limits, the target maneuvers are unknown but continuous and bounded.Assumption 3.
Actuators can respond to guidance commands in real time.Assumption 4.
The vertical acceleration of a missile afforded by actuators is no more than 300 m/s2.Lemma 1 [19].
Suppose thatVx is a C1 smoothing positive function defined on U∈ℝn. For any parameters β1>0 and β2∈0,1, if there always exists a function defined on U∈ℝn that satisfies
(11)V̇x+β1Vβ2x≤0,then there must exist a region U0∈ℝn such that any Vx that starts from U0∈ℝn will approach to Vx≡0 in finite time Treach. Moreover, this time Treach is governed by
(12)Treach≤V1−β2x0β11−β2,where Vx0 is the initial value of Vx.Lemma 2 [20].
Suppose a function can be described as(13)fx=xTAx,where x=x1,x2,⋯,xnT∈ℝn and A is a positive definite nonsingular matrix that is radially unbounded. The proposed function fx satisfies
(14)λminAx2≤fx≤λmaxAx2,where λminA and λmaxA denote the minimum and the maximum eigenvalues, respectively. Moreover, x=xTx∈R is the Euclid norm.Lemma 3 [21].
For any givenx∈ℝ and y∈ℝ, with c>0 and d>0, the following is satisfied:
(15)xcyd≤cc+dxc+d+dc+dxc+d.Lemma 4 [22].
Consider a cascaded system which is formulated as(16)ẋ1=ft,x1,x2=f1t,x1+gt,x1,x2,ẋ2=f2t,x2,where x1∈ℝn, x2∈ℝm, f1t,x1=ft,x1,0, and gt,x1,x2=ft,x1,x2−ft,x1,0. Assume that the subsystems ẋ1=f1t,x1 and ẋ2=f2t,x2 are uniformly globally finite-time stable (UGFTS). For arbitrary-fixed and bounded x2, if there exists a positive definite FTB function Bt,x1:ℝ≥0×ℝn→ℝ≥0, which satisfies Bt,x14≤β6Bt,x1, ∀t≥t0≥0, where β6:ℝ≥0→ℝ≥0 is a nondecreasing function satisfying β6a≥0 and ∫a∞1/β6sds=∞ for some constant a>0, cascaded system (16) is UGFTS.


## 2.1. Planar Mathematical Model of the Engagement Phase

Throughout the paper, the research object is assumed to satisfy the following hypothesizes: (i) the mass of the missile is in uniform distribution, (ii) the no roll or roll rate is small enough, and (iii) the mechanical properties of the missile are similar in every direction perpendicular to the roll axis. As a result, the missile can be regarded as a point mass. To simplify the problem, the relationship between the missile and the target during the engagement phase can be taken into account as a planar interception, which is illustrated in Figure1.Figure 1
The planar model of the relationship between the missile and the target.From Figure1, one can conclude that
(1)ṙ=VTcosγT−λ−VMcosγM−λ,(2)λ̇=VTsinγT−λ−VMcosγM−λr,(3)γ̇M=aMVM,(4)γ̇T=aTVT,where M denotes the missile and T denotes the target; VT and VM denote the velocities of the target and the missile, respectively; aT and aM denote the accelerations of the target and the missile, respectively; r and ṙ denote the distance and its derivative, respectively, between the missile and the target; λ and λ̇ denote the LOS angle and the LOS angular rate, respectively; γM and γ̇M denote the heading angle and the heading angular rate of the missile, respectively; γT and γ̇T denote the heading angle and the heading angular rate of the target, respectively.Taking the derivative of equation (1) and equation (2) with respect to time yields
(5)r¨=rλ̇2+aTr−aMr,(6)λ¨=−2ṙλ̇r+aTλr−aMλr.Here,aTr=aTsinλ−γT and aMr=aMsinλ−γM denote accelerations following the LOS direction of the target and the missile, respectively. aTλ=aTcosλ−γT and aMλ=aMcosλ−γM denote accelerations perpendicular to the LOS direction of the target and the missile, respectively. This completes the planar mathematical model.Remark 1.
For a missile controlled by active forces, equation (5) and equation (6) must be considered simultaneously during the process of guidance law design. However, for a missile only controlled by aerodynamic forces, the velocity in the LOS direction can be regard as constant. Hence, using only equation (6) to design the guidance law is adequate.


## 2.2. Strategy of Interception

According to the zeroing LOS angular rate principle, assuming that the LOS angular rate will converge to zero when collision occurs, from equation (2), one can infer that
(7)VTsinγTf−λf=VMsinγMf−λf,where the subscript f denotes the values of the relevant parameters at terminal time.Denote impact angleθimp as the following equation:
(8)θimp=γTf−γMf.Substituting equation (8) into equation (7) yields
(9)VTsinγTf−λf−VMsinγTf−θimp−λf=0.By assuming thatVT<VM, solving equation (9) yields
(10)λf=γTf−tan−1sinθimpcosθimp−VT/VM.From equation (10), one can conclude that, for any given impact angle θimp, there must exist one and one only relevant LOS angle. In other words, the problem of impact angle constraints can be transformed as the tracking LOS angle problem. We can design a Lyapunov approach to drive the LOS angle λ to converge to the desired LOS angle λd and the LOS angular rate λ̇ to converge to zero in finite time to solve this problem.


## 2.3. Some Assumptions and Lemmas

The following assumptions and lemmas are used throughout this paper.Assumption 1.
There must exist a minimum distancermin between the missile and the target. For any given r, the following is required: r≥rmin.Remark 3.
Because of the length of the missile and the length of the target from the shells to the point masses, Assumption1 is reasonable.Assumption 2.
Because of the physical limits, the target maneuvers are unknown but continuous and bounded.Assumption 3.
Actuators can respond to guidance commands in real time.Assumption 4.
The vertical acceleration of a missile afforded by actuators is no more than 300 m/s2.Lemma 1 [19].
Suppose thatVx is a C1 smoothing positive function defined on U∈ℝn. For any parameters β1>0 and β2∈0,1, if there always exists a function defined on U∈ℝn that satisfies
(11)V̇x+β1Vβ2x≤0,then there must exist a region U0∈ℝn such that any Vx that starts from U0∈ℝn will approach to Vx≡0 in finite time Treach. Moreover, this time Treach is governed by
(12)Treach≤V1−β2x0β11−β2,where Vx0 is the initial value of Vx.Lemma 2 [20].
Suppose a function can be described as(13)fx=xTAx,where x=x1,x2,⋯,xnT∈ℝn and A is a positive definite nonsingular matrix that is radially unbounded. The proposed function fx satisfies
(14)λminAx2≤fx≤λmaxAx2,where λminA and λmaxA denote the minimum and the maximum eigenvalues, respectively. Moreover, x=xTx∈R is the Euclid norm.Lemma 3 [21].
For any givenx∈ℝ and y∈ℝ, with c>0 and d>0, the following is satisfied:
(15)xcyd≤cc+dxc+d+dc+dxc+d.Lemma 4 [22].
Consider a cascaded system which is formulated as(16)ẋ1=ft,x1,x2=f1t,x1+gt,x1,x2,ẋ2=f2t,x2,where x1∈ℝn, x2∈ℝm, f1t,x1=ft,x1,0, and gt,x1,x2=ft,x1,x2−ft,x1,0. Assume that the subsystems ẋ1=f1t,x1 and ẋ2=f2t,x2 are uniformly globally finite-time stable (UGFTS). For arbitrary-fixed and bounded x2, if there exists a positive definite FTB function Bt,x1:ℝ≥0×ℝn→ℝ≥0, which satisfies Bt,x14≤β6Bt,x1, ∀t≥t0≥0, where β6:ℝ≥0→ℝ≥0 is a nondecreasing function satisfying β6a≥0 and ∫a∞1/β6sds=∞ for some constant a>0, cascaded system (16) is UGFTS.


## 3. Guidance Law Design and Stability Analysis

### 3.1. 2-OB Design and Stability Analysis

According to Assumption2, the acceleration of the target is unknown. To estimate the target acceleration, based on second-order SMC theory, an observer is proposed as follows:
(17)q^̇=a^̇Tλ+h1q−q^1−1/υsignq−q^−ṙλ̇−aMλ,a^̇Tλ=h2q−q^1−2/υsignq−q^,where q=rλ̇, h1>0, h2>0, and υ>2 are the design parameters; q^ and a^Tλ are the estimated values of q and aTλ, respectively.Proposition 1.
Considering system equations (1)–(4) and observer equation (17), the estimated errors denoted as e1=q−q^ and e2=aTλ−a^Tλ will approach the following area in finite time:
(18)e≤ȧTλmaxBλminMυ−1/υ−2,where e=e1,e2T and
(19)M=h1h2+h13υ−1υ−h12υ−1υ−h12υ−1υh1υ−1υ,B=−h1,2T.
λminM is denoted as the minimum eigenvalue of matrix M; similarly, λmaxM is denoted as the maximum eigenvalue of matrix M.Proof of Proposition 1.
See AppendixA.


### 3.2. Sliding Manifold Design

By denotingε1=λ−λd and ε2=λ̇−λ̇d=λ̇, a novel nonsingular switchable sliding manifold is presented as
(20)s=ε2+k1ε1+k2αε1,where k1>0 and k2>0 are the design parameters and αx1 is governed by
(21)αε1=ε1τ1/τ2signε1,ifs¯=0ors¯≠0,ε1≥μ,b1ε1+b2signε1ε12,ifs¯≠0,ε1<μ,with b1=2−τ1/τ2μτ1/τ2−1, b2=2−τ1/τ2μτ1/τ2−2, and s¯=ε2+k1ε1+k2ε1p/qsignε1. τ1 is an even integer, τ2 is an even integer, μ is a very small constant, and sign⋅ denotes the sigmoid function, which is governed by
(22)signx=−1,ifx<0,0,ifx=0,1,ifx>0.(23)s¯=ε1+k−q/pε2q/p,where parameter k is a positive constant.Remark 4.
The design parametersb1 and b2 are properly selected according to the above discussion such that the switching manifold equation (20) is continuous and differentiable.Remark 5.
Note that to avoid singularity, this switching manifold will switch to a novel linear sliding mode (LSM) switching manifold when the system stateε1 is very small and the conventional fast terminal sliding mode (TSM) switching manifold is not equal to zero [23]. In addition to this switching manifold, another nonlinear terminal sliding mode (NTSM) switching manifold is governed by [24].Remark 6.
In comparison with the conventional NTSM switching manifold equation (22), the proposed switching manifold uses a switchable design technique to avoid the singularity phenomenon. When the system trajectory is close to zero, the switching manifold will switch from the terminal switching manifold to the linear switching manifold. Moreover, when the system trajectory is far away from the switching manifold, the linear term k1ε1 will accelerate the convergent rate and the nonlinear term k2αε1 will play a leading role. Hence, compared with the conventional NTSM switching manifold equation (22), the proposed switching manifold shows better convergent performance if the parameters are properly selected.Proposition 2.
For an arbitrary second-order certain system (such as system equation (6)) or uncertain system, if the proposed NTSM switching manifold s=0 is achieved, then the system states ε1 and ε2 will converge to zero in finite time.Proof of Proposition 2.
See AppendixB.


### 3.3. Finite-Time Convergent Guidance Law Design

Taking the derivative of equation (19) with respect to time yields
(24)ṡ=ε̇2+k1ε2+k2α̇ε1,where the third term α̇ε1 is governed by
(25)α̇ε1=p/qε1p/q−1ε2,ifs¯=0ors¯≠0,ε1≥μ,b1ε2+2b2signε1ε1ε2,ifs¯≠0,ε1<μ.For the convenience of following research, equation (20) can be rewritten as
(26)ṡε1,ε2,t=fε1,ε2,t+bε1,ε2,taMλ,with
(27)fε1,ε2,t=−2ṙλ̇/r+aTλr+k1ε̇+k2p/qε1p/q−1ε2,ifs¯=0ors¯≠0,ε1≥μ−2ṙλ̇/r+aTλr+k1ε̇+k2b1ε2+2b2signε1ε1ε2,ifs¯≠0,ε1<μ,bε1,ε2,t=−1r.By replacingaTλ with a^Tλ, the estimated state function f^ε1,ε2,t can be described as
(28)f^ε1,ε2,t=−2ṙλ̇/r+a^Tλr+k1ε̇+k2p/qε1p/q−1ε2,ifs¯=0ors¯≠0,ε1≥μ−2ṙλ̇/r+a^Tλr+k1ε̇+k2b1ε2+2b2signε1ε1ε2,ifs¯≠0,ε1<μ.The proposed switchable controller can be described as(29)aMλ=−b−1ε1,ε2,tf^ε1,ε2,t+c1s1−1/γsigns−c2ς,ς̇=bε1,ε2,ts1−2/γsigns,where c1 and c2 are positive constants and γ>2 is a constant.Proposition 3.
Considering the proposed second-order system equation (16), the proposed controller equation (28) can drive the system states to converge to the switching manifold in finite time.Proof of Proposition 3.
For an “observer-controller” system, the conventional separation principle is not reasonable. The proof should be divided into two steps. The system’s boundedness will be illustrated via the FTB [22] function method in Step I, and the feature FTC of the LOS angular rate will be illustrated in Step II.Step I.
Substituting equation (29) into equation (26) yields
(30)ṡ=aTλ−a^Tλr−k1rs1−1/γsigns−k2r∫s1−2/γsignsrdt.
For simplicity, denote two auxiliary variables as(31)ω1=s,ω2=aTλ−a^Tλ−k2∫s1−2/γsignsrdt.
Taking the derivatives of equation (31) with respect to time yields
(32)ω̇1=ω2r−k1rω11−1/γsignω1,ω̇2=ȧTλ−a^̇Tλ−k2rω21−2/γsignω1.
Denoting the auxiliary vectorω=ω11−1/γsignω1,ω2T and taking the following FTB function into account yield:
(33)V1=ωTω=ω12γ−1/γ+ω22.
It is easy to verify thatV1∈ℝ2 is continuous within its domain of definition, except for the set Ψ=ω1,ω2∈ℝ2ω1=0. However, it follows from ω1=0 and ω2≠0 that ω̇1=ω2≠0 and the trajectories of system states will pass through Ψ rather than stay in, until system states reach zero. Thus, the proposed Lyapunov function V1 can be used to verify the property of FTB of the proposed guidance.
Taking the time derivative ofV1 yields
(34)V̇1=2γ−1γω11−2/γsignω1ω2r−k1rω11−1/γsignω1+2ω2ȧTλ−a^̇Tλ−k2rω11−2/γsignω1≤2γ−1γω11−2/γsignω1ω2r+2ω2ȧTλ−a^̇Tλ−k2rω11−2/γsignω1≤2γ−1γω11−2/γsignω1ω2r+2ω2ȧTλ−a^̇Tλ+2k2rω11−2/γω2≤2γ−1γω11−2/γsignω1ω2rmin+2ω2ȧTλ−a^̇Tλ+2k2rminω11−2/γω2.
According to Lemma3 and the average value of the inequality, one can conclude that
(35)V̇1≤2γ−1γrminγ−22γ−2ω12γ−1/γ+γ2γ−2ω22γ−1/γ+ω22+ȧTλ−a^̇Tλ2+2k2γrminγ−22γ−2ω12γ−1/γ+γ2γ−2ω22γ−1/γ.
Consider the following two cases.Case 1.
Ifω2≤1 is satisfied, it follows from 2γ−1/γ∈1,2 that ω22γ−1/γ≤ω22. Substituting this inequality into equation (30) yields
(36)V̇1≤1rminγ−2γ+k2γ−2γω12p−1/p+1+1rmin1+k2γγ−1ω22+ȧTλ−a^̇Tλ2≤K1V1+ȧTλ−a^̇Tλ2,with K1=max1/rminγ−2/γ+k2γ−2/γ−1,1+1/rmink2γ/γ−1.Case 2.
Ifω2≥1 is satisfied, it follows from 2γ−1/γ∈1,2 that ω22γ−1/γ≤1. Substituting this inequality into equation (34) yields
(37)V̇1≤1rminγ−2γ+k2γ−2γω12p−1/p+1+1rmin1+k2γγ−1+ω22+ȧTλ−a^̇Tλ2≤K2V1+1rmin1+k2γγ−1+ȧTλ−a^̇Tλ2,with K1=max1/rminγ−2/γ+k2γ−2/γ−1,1.According to Proposition1, ȧTλ−a^̇Tλ is globally bounded. In other words, there exists a positive constant κ that satisfies ȧTλ−a^̇Tλ≤κ. Combined with the results of Case 1 and Case 2, one can conclude that
(38)V̇1≤KV1+L,where K=maxK1,K2 and L=1/rmin1+k2γ/γ−1+κ2.Hence, in any time range of0,t, solving inequality (35) yields
(39)V1≤V10+LKeKt−LK,where V10 denotes the initial value of V1. This completes the proof of the boundedness of the system.Step II.
According to Lemma1, the estimated target acceleration a^Tλ will converge into a small region around the real target acceleration a^̇Tλ in finite time. Hence, equation (32) can be rewritten as
(40)ω̇1=ω2r−k1rω11−1/γsignω1,ω̇2=−k2rω21−2/γsignω1.To prove the finite-time stability, the selected Lyapunov function is governed by(41)V2=c2γγ−1ω121−1/γ+12ω22+12k1ω11−1/γsignω1−ω22.Similar toV1, V2 is continuous except for Ψ=ω1,ω2∈ℝ2ω1=0 and can be used to verify the property of FTC.Taking the derivative of equation (32) with respect to time yields
(42)V̇2=−ω1−1/γc1c2ω12γ−1/γ+γ−1γc13ω12γ−1/γ−2γ−1γc12ω1γ−1/γsignω1ω2+γ−1γc1ω22.Equation (42) can be rewritten as
(43)V̇2=−ω1−1/γωTPω,with
(44)P=c1c2+c13γ−1γ−c12γ−1γ−c12γ−1γc1γ−1γ.Since parametersc1 and c2 are positive constants and γ>2, it is easy to verify that matrix P is positive definite.Equation (41) can be rewritten as
(45)V2=ωTQω,with
(46)Q=12c2γγ−1+c12−c1−c12.Sincec1 and c2 are positive constants and γ>2, it is easy to verify that matrix Q is positive definite and radial unbounded. According to Lemma 2, one can obtain
(47)λminQω2≤V2≤λmaxQω2.It follows fromω=ω12γ−1/γ+ω22≥ω1γ−1/r that ω11/γ≥ω−1/γ−1. Combining equation (43) and equation (45), one can conclude that
(48)V̇2≤−ω−1/γ−1λminPω2≤−λminPω2γ−3/γ−1≤−λminPλmaxQ2γ−3/2γ−2V22γ−3/2γ−2.Since2γ−3/2γ−2∈0,0.5, according to Lemma 1, the system states of equation (6) can converge to zero in finite time. This completes the proof.Remark 7.
A FTB function of system equation (6) and observer equation (17) with a certain upper bound is presented in Step I, and the UGFTS property of the proposed guidance law is demonstrated in Step II. From Assumption 2, one can imply that the observer is UGFTS. Finally, according to Lemma 4, system equation (6) with observer equation (17) and controller equation (29) is UGFTS.


## 3.1. 2-OB Design and Stability Analysis

According to Assumption2, the acceleration of the target is unknown. To estimate the target acceleration, based on second-order SMC theory, an observer is proposed as follows:
(17)q^̇=a^̇Tλ+h1q−q^1−1/υsignq−q^−ṙλ̇−aMλ,a^̇Tλ=h2q−q^1−2/υsignq−q^,where q=rλ̇, h1>0, h2>0, and υ>2 are the design parameters; q^ and a^Tλ are the estimated values of q and aTλ, respectively.Proposition 1.
Considering system equations (1)–(4) and observer equation (17), the estimated errors denoted as e1=q−q^ and e2=aTλ−a^Tλ will approach the following area in finite time:
(18)e≤ȧTλmaxBλminMυ−1/υ−2,where e=e1,e2T and
(19)M=h1h2+h13υ−1υ−h12υ−1υ−h12υ−1υh1υ−1υ,B=−h1,2T.
λminM is denoted as the minimum eigenvalue of matrix M; similarly, λmaxM is denoted as the maximum eigenvalue of matrix M.Proof of Proposition 1.
See AppendixA.


## 3.2. Sliding Manifold Design

By denotingε1=λ−λd and ε2=λ̇−λ̇d=λ̇, a novel nonsingular switchable sliding manifold is presented as
(20)s=ε2+k1ε1+k2αε1,where k1>0 and k2>0 are the design parameters and αx1 is governed by
(21)αε1=ε1τ1/τ2signε1,ifs¯=0ors¯≠0,ε1≥μ,b1ε1+b2signε1ε12,ifs¯≠0,ε1<μ,with b1=2−τ1/τ2μτ1/τ2−1, b2=2−τ1/τ2μτ1/τ2−2, and s¯=ε2+k1ε1+k2ε1p/qsignε1. τ1 is an even integer, τ2 is an even integer, μ is a very small constant, and sign⋅ denotes the sigmoid function, which is governed by
(22)signx=−1,ifx<0,0,ifx=0,1,ifx>0.(23)s¯=ε1+k−q/pε2q/p,where parameter k is a positive constant.Remark 4.
The design parametersb1 and b2 are properly selected according to the above discussion such that the switching manifold equation (20) is continuous and differentiable.Remark 5.
Note that to avoid singularity, this switching manifold will switch to a novel linear sliding mode (LSM) switching manifold when the system stateε1 is very small and the conventional fast terminal sliding mode (TSM) switching manifold is not equal to zero [23]. In addition to this switching manifold, another nonlinear terminal sliding mode (NTSM) switching manifold is governed by [24].Remark 6.
In comparison with the conventional NTSM switching manifold equation (22), the proposed switching manifold uses a switchable design technique to avoid the singularity phenomenon. When the system trajectory is close to zero, the switching manifold will switch from the terminal switching manifold to the linear switching manifold. Moreover, when the system trajectory is far away from the switching manifold, the linear term k1ε1 will accelerate the convergent rate and the nonlinear term k2αε1 will play a leading role. Hence, compared with the conventional NTSM switching manifold equation (22), the proposed switching manifold shows better convergent performance if the parameters are properly selected.Proposition 2.
For an arbitrary second-order certain system (such as system equation (6)) or uncertain system, if the proposed NTSM switching manifold s=0 is achieved, then the system states ε1 and ε2 will converge to zero in finite time.Proof of Proposition 2.
See AppendixB.


## 3.3. Finite-Time Convergent Guidance Law Design

Taking the derivative of equation (19) with respect to time yields
(24)ṡ=ε̇2+k1ε2+k2α̇ε1,where the third term α̇ε1 is governed by
(25)α̇ε1=p/qε1p/q−1ε2,ifs¯=0ors¯≠0,ε1≥μ,b1ε2+2b2signε1ε1ε2,ifs¯≠0,ε1<μ.For the convenience of following research, equation (20) can be rewritten as
(26)ṡε1,ε2,t=fε1,ε2,t+bε1,ε2,taMλ,with
(27)fε1,ε2,t=−2ṙλ̇/r+aTλr+k1ε̇+k2p/qε1p/q−1ε2,ifs¯=0ors¯≠0,ε1≥μ−2ṙλ̇/r+aTλr+k1ε̇+k2b1ε2+2b2signε1ε1ε2,ifs¯≠0,ε1<μ,bε1,ε2,t=−1r.By replacingaTλ with a^Tλ, the estimated state function f^ε1,ε2,t can be described as
(28)f^ε1,ε2,t=−2ṙλ̇/r+a^Tλr+k1ε̇+k2p/qε1p/q−1ε2,ifs¯=0ors¯≠0,ε1≥μ−2ṙλ̇/r+a^Tλr+k1ε̇+k2b1ε2+2b2signε1ε1ε2,ifs¯≠0,ε1<μ.The proposed switchable controller can be described as(29)aMλ=−b−1ε1,ε2,tf^ε1,ε2,t+c1s1−1/γsigns−c2ς,ς̇=bε1,ε2,ts1−2/γsigns,where c1 and c2 are positive constants and γ>2 is a constant.Proposition 3.
Considering the proposed second-order system equation (16), the proposed controller equation (28) can drive the system states to converge to the switching manifold in finite time.Proof of Proposition 3.
For an “observer-controller” system, the conventional separation principle is not reasonable. The proof should be divided into two steps. The system’s boundedness will be illustrated via the FTB [22] function method in Step I, and the feature FTC of the LOS angular rate will be illustrated in Step II.Step I.
Substituting equation (29) into equation (26) yields
(30)ṡ=aTλ−a^Tλr−k1rs1−1/γsigns−k2r∫s1−2/γsignsrdt.
For simplicity, denote two auxiliary variables as(31)ω1=s,ω2=aTλ−a^Tλ−k2∫s1−2/γsignsrdt.
Taking the derivatives of equation (31) with respect to time yields
(32)ω̇1=ω2r−k1rω11−1/γsignω1,ω̇2=ȧTλ−a^̇Tλ−k2rω21−2/γsignω1.
Denoting the auxiliary vectorω=ω11−1/γsignω1,ω2T and taking the following FTB function into account yield:
(33)V1=ωTω=ω12γ−1/γ+ω22.
It is easy to verify thatV1∈ℝ2 is continuous within its domain of definition, except for the set Ψ=ω1,ω2∈ℝ2ω1=0. However, it follows from ω1=0 and ω2≠0 that ω̇1=ω2≠0 and the trajectories of system states will pass through Ψ rather than stay in, until system states reach zero. Thus, the proposed Lyapunov function V1 can be used to verify the property of FTB of the proposed guidance.
Taking the time derivative ofV1 yields
(34)V̇1=2γ−1γω11−2/γsignω1ω2r−k1rω11−1/γsignω1+2ω2ȧTλ−a^̇Tλ−k2rω11−2/γsignω1≤2γ−1γω11−2/γsignω1ω2r+2ω2ȧTλ−a^̇Tλ−k2rω11−2/γsignω1≤2γ−1γω11−2/γsignω1ω2r+2ω2ȧTλ−a^̇Tλ+2k2rω11−2/γω2≤2γ−1γω11−2/γsignω1ω2rmin+2ω2ȧTλ−a^̇Tλ+2k2rminω11−2/γω2.
According to Lemma3 and the average value of the inequality, one can conclude that
(35)V̇1≤2γ−1γrminγ−22γ−2ω12γ−1/γ+γ2γ−2ω22γ−1/γ+ω22+ȧTλ−a^̇Tλ2+2k2γrminγ−22γ−2ω12γ−1/γ+γ2γ−2ω22γ−1/γ.
Consider the following two cases.Case 1.
Ifω2≤1 is satisfied, it follows from 2γ−1/γ∈1,2 that ω22γ−1/γ≤ω22. Substituting this inequality into equation (30) yields
(36)V̇1≤1rminγ−2γ+k2γ−2γω12p−1/p+1+1rmin1+k2γγ−1ω22+ȧTλ−a^̇Tλ2≤K1V1+ȧTλ−a^̇Tλ2,with K1=max1/rminγ−2/γ+k2γ−2/γ−1,1+1/rmink2γ/γ−1.Case 2.
Ifω2≥1 is satisfied, it follows from 2γ−1/γ∈1,2 that ω22γ−1/γ≤1. Substituting this inequality into equation (34) yields
(37)V̇1≤1rminγ−2γ+k2γ−2γω12p−1/p+1+1rmin1+k2γγ−1+ω22+ȧTλ−a^̇Tλ2≤K2V1+1rmin1+k2γγ−1+ȧTλ−a^̇Tλ2,with K1=max1/rminγ−2/γ+k2γ−2/γ−1,1.According to Proposition1, ȧTλ−a^̇Tλ is globally bounded. In other words, there exists a positive constant κ that satisfies ȧTλ−a^̇Tλ≤κ. Combined with the results of Case 1 and Case 2, one can conclude that
(38)V̇1≤KV1+L,where K=maxK1,K2 and L=1/rmin1+k2γ/γ−1+κ2.Hence, in any time range of0,t, solving inequality (35) yields
(39)V1≤V10+LKeKt−LK,where V10 denotes the initial value of V1. This completes the proof of the boundedness of the system.Step II.
According to Lemma1, the estimated target acceleration a^Tλ will converge into a small region around the real target acceleration a^̇Tλ in finite time. Hence, equation (32) can be rewritten as
(40)ω̇1=ω2r−k1rω11−1/γsignω1,ω̇2=−k2rω21−2/γsignω1.To prove the finite-time stability, the selected Lyapunov function is governed by(41)V2=c2γγ−1ω121−1/γ+12ω22+12k1ω11−1/γsignω1−ω22.Similar toV1, V2 is continuous except for Ψ=ω1,ω2∈ℝ2ω1=0 and can be used to verify the property of FTC.Taking the derivative of equation (32) with respect to time yields
(42)V̇2=−ω1−1/γc1c2ω12γ−1/γ+γ−1γc13ω12γ−1/γ−2γ−1γc12ω1γ−1/γsignω1ω2+γ−1γc1ω22.Equation (42) can be rewritten as
(43)V̇2=−ω1−1/γωTPω,with
(44)P=c1c2+c13γ−1γ−c12γ−1γ−c12γ−1γc1γ−1γ.Since parametersc1 and c2 are positive constants and γ>2, it is easy to verify that matrix P is positive definite.Equation (41) can be rewritten as
(45)V2=ωTQω,with
(46)Q=12c2γγ−1+c12−c1−c12.Sincec1 and c2 are positive constants and γ>2, it is easy to verify that matrix Q is positive definite and radial unbounded. According to Lemma 2, one can obtain
(47)λminQω2≤V2≤λmaxQω2.It follows fromω=ω12γ−1/γ+ω22≥ω1γ−1/r that ω11/γ≥ω−1/γ−1. Combining equation (43) and equation (45), one can conclude that
(48)V̇2≤−ω−1/γ−1λminPω2≤−λminPω2γ−3/γ−1≤−λminPλmaxQ2γ−3/2γ−2V22γ−3/2γ−2.Since2γ−3/2γ−2∈0,0.5, according to Lemma 1, the system states of equation (6) can converge to zero in finite time. This completes the proof.Remark 7.
A FTB function of system equation (6) and observer equation (17) with a certain upper bound is presented in Step I, and the UGFTS property of the proposed guidance law is demonstrated in Step II. From Assumption 2, one can imply that the observer is UGFTS. Finally, according to Lemma 4, system equation (6) with observer equation (17) and controller equation (29) is UGFTS.


## 4. Case Study

In this section, numerical simulations are performed to demonstrate efficiency and effectiveness of the proposed guidance law for missiles that intercept three types of targets during terminal guidance. The simulations are performed with the MATLAB platform by using the fourth-order Runge-Kutta solver with a fixed step size of 0.001 s.


### 4.1. Simulation Setup

Verify the effectiveness of the proposed guidance law in the presence of a two-dimension environment. The required initial conditions are selected as follows: (1) the initial range isr0=7071 m, (2) target velocity is VT=200 m/s, (3) interceptor velocity is VM=400 m/s, (4) initial LOS angle is λ0=45 deg, (5) initial heading angle of the missile is γM0=45 deg, (6) initial heading angle of the target is γT0=180 deg, and (7) values of the design parameters are given in Table 1.Table 1
Values of the design parameters.
Parameter
k1
k2
c1
c2
h1
h2
γ
υ
μ
Value
5
5
600
500
300
200
2.1
2.5
0.3


### 4.2. Simulation Results

Verify the effectiveness of the proposed guidance law in the presence of a two-dimension environment. To strengthen the universality of the proposed planar guidance law, three performances of the target maneuvers are considered, as described in the following: case 1: the target maneuver is constant,aT=50 m/s2, case 2: the target maneuver satisfies the sinusoidal components, aT=50sin0.5t m/s2, and case 3: the target maneuver is random, as illustrated in Figure 2.Figure 2
The target maneuver in case 3.The simulation results include trajectories of the missile and the target, missile accelerations, LOS angles and angular rates, sliding manifolds, and estimated target maneuvers. Figure3 is for case 1, Figure 4 is for case 2, and Figure 5 is for case 3. As shown in Figures 3(a), 4(a), and 5(a), one can see clearly that the missile can intercept the target accurately in the presence of different target maneuvers and different impact angles under the proposed guidance law. In Figures 3(b), 4(b), and 5(b), the missile accelerations are limited to 300 m/s2 and are chattering free. Figures 3(c), 4(c), and 5(c) and Figures 3(d), 4(d), and 5(d) imply that the LOS angles converge to the desired values at terminal time and the LOS angular rates converge to zero at terminal time. Figures 3(e), 4(e), and 5(e) give the curves of the sliding manifolds. Figures 3(f), 4(f), and 5(f) show the real values of the unknowns and their estimated values; clearly, every estimated value will reach to the related real value and sliding on its surface. Figures 3(g), 4(g), and 5(g) depict the third terms of equation (24). These results verify the efficiency and effectiveness of the proposed planar guidance law.Figure 3
Simulation results of case 1.
(a)
Trajectories
(b)
Missile accelerations
(c)
LOS angles
(d)
LOS angular rates
(e)
Sliding manifolds
(f)
Estimations ofaTλ
(g)
The third term in equation (24)Figure 4
Simulation results of case 2.
(a)
Trajectories
(b)
Missile accelerations
(c)
LOS angles
(d)
LOS angular rates
(e)
Sliding manifolds
(f)
Estimations ofaTλ
(g)
The third term in equation (24)Figure 5
Simulation results of case 3.
(a)
Trajectories
(b)
Missile accelerations
(c)
LOS angles
(d)
LOS angular rates
(e)
Sliding manifolds
(f)
Estimations ofaTλ
(g)
The third term in equation (24)Note that there exists a divergent phenomenon in some figures, such as in Figures4(d) and 5(d). This phenomenon results from the inherent property of guidance. When the interceptor is very close to the target, r is very small or even regarded as zero. Considering that r is contained in denominators in the system of equation (6), the terrible influence from r→0 is difficult to affect. However, by considering that r has a minimum value rmin (Assumption 1), the divergent phenomenon at the end of the engagement phase can be ignored; thus, the proposed guidance law still meets the requirements in actual practice.Next, for the purpose of further demonstration of the efficiency and effectiveness of the proposed guidance law, the NTSM guidance law in [20] shown below is employed for comparison:
(49)aMλ=−2ṙλ̇+rβαe22−αsigne2+d+v1s¯1−1/psigns¯+v2ξ,ξ̇=e2α−1s¯1−2/prsigns¯,s¯=e1+1βe2αsigne2,d=aM+aTλ−aMλ.Here, assume that knowledge of the target accelerationaTλ in the NTSM guidance law can be obtained in real time. Moreover, the design parameters α, β, p, v1, and v2 are chosen to be the same as those in [22]. In this comparison case, the target maneuver is chosen as aT=−50sin0.5t m/s2 and the desired final LOS angles are selected as λd=30 deg and λd=60 deg.The simulation results of the comparison are illustrated in Figure6. Similar to the above simulation cases, Figures 6(a) and 6(b) demonstrate that the missile intercepts the target with high accuracy and that the actuator can provide enough acceleration during the engagement phase. Figures 6(c) and 6(d) show the superiority of the proposed guidance law. Although the two guidance laws can drive the LOS angle and its rate to converge on their desired values, the proposed guidance law achieves this goal more quickly in the presence of the same design parameters. This result verifies Remark 6.Remark 8.
In real practice, considering that the central processing units (CPUs) on the interceptors can only identify and generate simple instant signal, it is important to design discrete-time guidance laws [25]. Compared with the continuous sliding mode guidance law, however, the chattering phenomenon is much easier to occur and much more difficult to avoid. Thanks to the works in [26, 27], this problem has been addressed.Figure 6
Simulation results of comparison.
(a)
Trajectories
(b)
Missile accelerations
(c)
LOS angles
(d)
LOS angular rates


## 4.1. Simulation Setup

Verify the effectiveness of the proposed guidance law in the presence of a two-dimension environment. The required initial conditions are selected as follows: (1) the initial range isr0=7071 m, (2) target velocity is VT=200 m/s, (3) interceptor velocity is VM=400 m/s, (4) initial LOS angle is λ0=45 deg, (5) initial heading angle of the missile is γM0=45 deg, (6) initial heading angle of the target is γT0=180 deg, and (7) values of the design parameters are given in Table 1.Table 1
Values of the design parameters.
Parameter
k1
k2
c1
c2
h1
h2
γ
υ
μ
Value
5
5
600
500
300
200
2.1
2.5
0.3


## 4.2. Simulation Results

Verify the effectiveness of the proposed guidance law in the presence of a two-dimension environment. To strengthen the universality of the proposed planar guidance law, three performances of the target maneuvers are considered, as described in the following: case 1: the target maneuver is constant,aT=50 m/s2, case 2: the target maneuver satisfies the sinusoidal components, aT=50sin0.5t m/s2, and case 3: the target maneuver is random, as illustrated in Figure 2.Figure 2
The target maneuver in case 3.The simulation results include trajectories of the missile and the target, missile accelerations, LOS angles and angular rates, sliding manifolds, and estimated target maneuvers. Figure3 is for case 1, Figure 4 is for case 2, and Figure 5 is for case 3. As shown in Figures 3(a), 4(a), and 5(a), one can see clearly that the missile can intercept the target accurately in the presence of different target maneuvers and different impact angles under the proposed guidance law. In Figures 3(b), 4(b), and 5(b), the missile accelerations are limited to 300 m/s2 and are chattering free. Figures 3(c), 4(c), and 5(c) and Figures 3(d), 4(d), and 5(d) imply that the LOS angles converge to the desired values at terminal time and the LOS angular rates converge to zero at terminal time. Figures 3(e), 4(e), and 5(e) give the curves of the sliding manifolds. Figures 3(f), 4(f), and 5(f) show the real values of the unknowns and their estimated values; clearly, every estimated value will reach to the related real value and sliding on its surface. Figures 3(g), 4(g), and 5(g) depict the third terms of equation (24). These results verify the efficiency and effectiveness of the proposed planar guidance law.Figure 3
Simulation results of case 1.
(a)
Trajectories
(b)
Missile accelerations
(c)
LOS angles
(d)
LOS angular rates
(e)
Sliding manifolds
(f)
Estimations ofaTλ
(g)
The third term in equation (24)Figure 4
Simulation results of case 2.
(a)
Trajectories
(b)
Missile accelerations
(c)
LOS angles
(d)
LOS angular rates
(e)
Sliding manifolds
(f)
Estimations ofaTλ
(g)
The third term in equation (24)Figure 5
Simulation results of case 3.
(a)
Trajectories
(b)
Missile accelerations
(c)
LOS angles
(d)
LOS angular rates
(e)
Sliding manifolds
(f)
Estimations ofaTλ
(g)
The third term in equation (24)Note that there exists a divergent phenomenon in some figures, such as in Figures4(d) and 5(d). This phenomenon results from the inherent property of guidance. When the interceptor is very close to the target, r is very small or even regarded as zero. Considering that r is contained in denominators in the system of equation (6), the terrible influence from r→0 is difficult to affect. However, by considering that r has a minimum value rmin (Assumption 1), the divergent phenomenon at the end of the engagement phase can be ignored; thus, the proposed guidance law still meets the requirements in actual practice.Next, for the purpose of further demonstration of the efficiency and effectiveness of the proposed guidance law, the NTSM guidance law in [20] shown below is employed for comparison:
(49)aMλ=−2ṙλ̇+rβαe22−αsigne2+d+v1s¯1−1/psigns¯+v2ξ,ξ̇=e2α−1s¯1−2/prsigns¯,s¯=e1+1βe2αsigne2,d=aM+aTλ−aMλ.Here, assume that knowledge of the target accelerationaTλ in the NTSM guidance law can be obtained in real time. Moreover, the design parameters α, β, p, v1, and v2 are chosen to be the same as those in [22]. In this comparison case, the target maneuver is chosen as aT=−50sin0.5t m/s2 and the desired final LOS angles are selected as λd=30 deg and λd=60 deg.The simulation results of the comparison are illustrated in Figure6. Similar to the above simulation cases, Figures 6(a) and 6(b) demonstrate that the missile intercepts the target with high accuracy and that the actuator can provide enough acceleration during the engagement phase. Figures 6(c) and 6(d) show the superiority of the proposed guidance law. Although the two guidance laws can drive the LOS angle and its rate to converge on their desired values, the proposed guidance law achieves this goal more quickly in the presence of the same design parameters. This result verifies Remark 6.Remark 8.
In real practice, considering that the central processing units (CPUs) on the interceptors can only identify and generate simple instant signal, it is important to design discrete-time guidance laws [25]. Compared with the continuous sliding mode guidance law, however, the chattering phenomenon is much easier to occur and much more difficult to avoid. Thanks to the works in [26, 27], this problem has been addressed.Figure 6
Simulation results of comparison.
(a)
Trajectories
(b)
Missile accelerations
(c)
LOS angles
(d)
LOS angular rates


## 5. Conclusion

This paper presented a chattering-free nonsingular finite-time convergent guidance law in the presence of impact angle constraints; more specifically, the target maneuvers are obtained by proposing a second-order SMC-based observer and singularity is avoided by proposing a switchable sliding manifold. A super twisting type of guidance law was proposed to force the LOS angle and angular rate to converge to the desired values in finite time. Furthermore, the proposed planar guidance was extended in three-dimension cases. Numerical simulation results demonstrated the aforementioned properties.



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*Source: 6024240-2019-04-07.xml*