This paper investigates the design of a missile seeker servo system combined with a guidance and control system. Firstly, a complete model containing a missile seeker servo system, missile guidance system, and missile control system (SGCS) was creatively proposed. Secondly, a designed high-order tracking differentiator (HTD) was used to estimate states of systems in real time, which guarantees the feasibility of the designed algorithm. To guarantee tracking precision and robustness, backstepping sliding-mode control was adopted. Aiming at the main problem of projectile motion disturbance, an adaptive radial basis function neural network (RBFNN) was proposed to compensate for disturbance. Adaptive RBFNN especially achieves online adjustment of residual error, which promotes estimation precision and eliminates the “chattering phenomenon”. The boundedness of all signals, including estimation error of high-order tracking differentiator, was especially proved via the Lyapunov stability theory, which is more rigorous. Finally, in considered scenarios, line of sight angle (LOSA)-tracking simulations were carried out to verify the tracking performance, and a Monte Carlo miss-distance simulation is presented to validate the effectiveness of the proposed method.

Based on the theory of fractional order calculus (FOC), a novel extended proportional guidance (EPN) law for intercepting the maneuvering target is proposed. In the first part, considering the memory function and filter characteristic of FOC, the novel extended PN guidance algorithm is developed based on the conventional PN after introducing the properties and operation rules of FOC. Further, with the help of FOC theory, the average load and ballistics characteristics of proposed guidance law are analyzed. Then, using the small offset kinematic model, the robustness of the new guidance law against autopilot parameters is studied theoretically by analyzing the sensitivity of the closed loop guidance system. At last, representative numerical results show that the designed guidance law obtains a better performance than the traditional PN for maneuvering target.

In the terminal guidance phase of intercepting aerial target, a guidance law, satisfying impact angle constraint, acceleration constraint, and second-order dynamic characteristic of interceptor autopilot, is designed based on the prescribed performance control and dynamic surface control method. Firstly, a two-dimensional plane interception model considering the dynamic characteristics of autopilot and input constraints is established. Furthermore, for the nonconstrained system, based on the dynamic surface control, the prescribed performance reaching law is used to ensure that the line-of-sight angle and the line-of-sight angle rate can converge to the prescribed range in finite time. At the same time, an adaptive law is used to estimate the uncertainty caused by target maneuver and autopilot. Then, aiming at the acceleration constraint, an auxiliary system is established to convert the restricted system into a nonrestricted system. The finite-time convergence of the terminal line-of-sight tracking error, the line-of-sight rate, and the uniform ultimate boundedness of the system are rigorously proved by Lyapunov stability theory. Finally, the simulation results show that the proposed guidance law can make the interceptor have better interception performance when attacking targets with different maneuvering forms.

To address the issue of jitter and oscillation of guidance command during multi-vehicle cooperative engagement with maneuvering platforms, this paper proposes a novel terminal guidance law with prescribed performance constraints for multiple cooperative vehicles, which explicitly considers both transient and steady-state performance. Firstly, based on the vehicle-target relative kinematics, with time and space as the main constraint indicators, a multi-vehicle cooperative guidance model is established in the inertial coordinate system. Secondly, combined with the sliding mode control theory, cooperative guidance laws are designed for both the line-of-sight (LOS) direction and the LOS normal direction, respectively, and the Lyapunov stability proof is given. Furthermore, to counteract the impact of target maneuvers on guidance performance, a non-homogeneous disturbance observer is designed to estimate target maneuver information that is difficult to obtain directly, which ensures that performance constraints are still satisfied under strong target maneuvering conditions. Simulation results demonstrate that the proposed guidance law enables multiple coordinated vehicles to successfully engage the target under different maneuvering modes, while satisfying the terminal time-space constraints. Compared with conventional sliding mode control methods exhibiting inherent chattering, the proposed approach employs a novel PPC-SMC hybrid structure to quantitatively constrain the transient convergence of cooperative errors. This structure enhances the multi-vehicle cooperative guidance performance by effectively eliminating chattering and oscillations in the guidance commands, thereby significantly improving the system’s transient behavior.

To address the challenges of strong nonlinearity, stringent terminal constraints, and the trade-off between computational efficiency and accuracy in the midcourse guidance trajectory optimization problem of aerodynamically controlled interceptors, this paper proposes a variable-discrete-scale sequential convex programming (SCP) method. Firstly, a dynamic model is established by introducing the range domain to replace the traditional time domain, thereby reducing the approximation error of the planned trajectory. Second, to overcome the critical issues of solution space restriction and trajectory divergence caused by terminal equality constraints, a terminal error-proportional relaxation approach is proposed. Subsequently, an improved second-order cone programming (SOCP) formulation is developed through systematic integration of three key techniques: terminal error-proportional relaxation, variable trust region, and path normalization. Finally, an initial trajectory generation algorithm is proposed, upon which a variable-discrete-scale optimization framework is constructed. This framework incorporates a residual-driven discrete-scale adaptation mechanism, which balances discretization errors and computational load. Numerical simulation results indicate that under large discretization scales, the computation time required by the improved SOCP is only about 5.4% of that of GPOPS-II. For small-discretization-scale optimization, the SCP method with the variable discretization framework demonstrates high efficiency, achieving comparable accuracy to GPOPS-II while reducing the computation time to approximately 7.4% of that required by GPOPS-II.

In midcourse guidance, strong constraints and dual-channel control coupling pose major challenges for trajectory optimization. To address this, this paper proposes an optimal guidance method based on terminal relaxation and range convex programming. The study first derived a range-domain dynamics model with the angle of attack and bank angle as dual control inputs, augmented with path constraints including heat flux limitations, to formulate the midcourse guidance optimization problem. A terminal relaxation strategy was then proposed to mitigate numerical infeasibility induced by rigid terminal constraints, thereby guaranteeing the solvability of successive subproblems. Through the integration of affine variable transformations and successive linearization techniques, the original nonconvex problem was systematically converted into a second-order cone programming (SOCP) formulation, with theoretical equivalence between the relaxed and original problems established under well-justified assumptions. Furthermore, a heuristic initial trajectory generation scheme was devised, and the solution was obtained via a sequential convex programming (SCP) algorithm. Numerical simulation results demonstrated that the proposed method effectively satisfies strict path constraints, successfully generates feasible midcourse guidance trajectories, and exhibits strong computational efficiency and robustness. Additionally, a systematic comparison was conducted to evaluate the impact of different interpolation methods and discretization point quantities on algorithm performance.