Figure - available from: Discrete Dynamics in Nature and Society
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Motion coordinate systems of the maneuverable reentry vehicle. This is the basic shape of the maneuverable reentry, with the tail of the main engine and the RCS nozzle.
Source publication
This paper presents a new parametric optimization design to solve a class of reaction control system (RCS) problem with discrete switching state, flexible working time, and finite-energy control for maneuverable reentry vehicles. Based on basic particle swarm optimization (PSO) method, an exponentially decreasing inertia weight function is introduc...
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Citations
... Burchett [14] used a genetic algorithm to optimize the design variables of the rocket pulse jet controller. Gui et al. [15] proposed a new parameter optimization design method using an improved particle swarm optimization algorithm to solve a class of reaction control system problems for maneuverable reentry vehicles. It can be seen that the intelligent algorithms show a good optimization calculation effect. ...
... When the single correction working time Δt is determined, the disturbance value Δδ caused by the correction action on the projectile's angle-of-attack can be calculated via Equation (15). When the correction is paused, the angle-of-attack increment tends to stabilize under the action of the gyroscopic moment and equatorial damping moment. ...
... The size of this value can be adjusted according to the flight state of the projectile before the correction. Considering that manufacturing errors or other factors may lead to a large angle-of-attack caused by correction action, Δδ max is set to 8° [15,21]. At the same time, the allowable impact point deviation ΔE a0 of the projectile is set to 10 m. ...
In order to make the new air duct structure trajectory correction projectile have good dynamic correction control effect, the control strategy of the projectile’s correction mechanism is studied in this paper. A design method of trajectory correction control strategy based on particle swarm optimization-cuckoo search (PSO-CS) hybrid algorithm is proposed to obtain the optimal control parameters that can make the projectile flight stable and correct accurately. Firstly, the mathematical model of the air duct structure projectile is established. Secondly, the multiobjective optimization problem is analyzed. The projectile’s correction control strategy optimization model is established by taking the start control time, the number of corrections, the correction working time, and the interval time as the control variables. The optimization model innovatively considers the influence of the correction action on the flight stability of the projectile and the influence of the start control time on the correction range. Finally, the PSO-CS hybrid algorithm is used to design the calculation method of the optimization model and solve the optimal correction working parameters. The simulation results indicate that the control strategy optimization model can be solved by the proposed calculation method. Moreover, optimal correction working parameters of the correction mechanism in the current state can be obtained. Compared with the results of using single PSO algorithm and CS algorithm, the correction scheme calculated by PSO-CS hybrid optimization algorithm is better. This correction control scheme can effectively reduce the impact point deviation and make the projectile flight stable. At the same time, the circular error probable (CEP) of the projectile after correction is reduced from 42.3 m to 4.6 m while the impact point dispersion is lowered. The research results show that the design method of correction control strategy proposed in this paper is effective for trajectory correction of the new air duct structure projectile.
... Consequently, the key problem to control HVP is that traditional high-power actuator cannot be equipped in the projectile with limited space. To solve this technical conundrum, some new concept actuators were presented, such as reaction control system (RCS) [5], [6], [7], canard rudder [8], [9], and plasma actuator (PA) [10], [11]. However, these actuators have some limitations. ...
This paper presents a series active disturbance rejection controller (ADRC) autopilot design scheme with mini pin actuators for nonlinear hyper velocity projectile (HVP) system. In order to accurately describe the flight dynamics of HVP, a new nonlinear model with mismatched disturbances is established considering the aerodynamic characteristics of mini pin actuators. For compensating mismatched disturbances, series ADRC method is incorporated into double-loop (angle loop and angular loop) autopilot design, i.e., in the angle loop mismatched disturbances are observed and compensated in the virtual control calculation; in the angular loop, the observed matched disturbances are compensated in the mini pin control. In addition, both the mismatched and matched disturbances are considered as lumped ones including external disturbances, model uncertainties, coupling terms, etc. Finally, comparative numerical simulations with some traditional nonlinear control methods indicate that the proposed series ADRC HVP system has good robustness performance.
The problem of near space vehicle (NSV) control has aroused widespread concern in recent years. However, optimal control parameters are not easy to obtain which still remains a pressing challenge. This paper addresses the issue of NSV control parameters optimization. First, the velocity control method based on an active disturbance rejection control (ADRC) technique for the longitudinal nonlinear model of the NSV is given. Then, an enhanced pigeon-inspired optimization algorithm with a golden-sine mutation mechanism and an opposition-based learning strategy (GOPIO) is presented to achieve control parameter optimization. A case study is conducted to prove the validity of the proposed method. Simulation results indicate that the local search ability is strengthened in GOPIO compared with traditional algorithms.
