Proceedings of the Institution of Mechanical Engineers,Part G: Journal of Aerospace Engineering

Based on L₂ optimal control allocation, an autopilot design approach is proposed for the missile with aerodynamic control surfaces and reaction jets. The control system involves a control allocator and a virtual control law. A robust sliding sector with a parameter update law is proposed to deal with unmatched parameter uncertainties and unknown disturbances in the system. Then a control law is designed to produce virtual control effort signals by using the robust adaptive sliding sector. In order to distribute the virtual signals to the aerodynamic control surfaces and reaction jets on the missile, a control allocator is designed by L₂ optimal control allocation strategy. Simulation results show that the missile control system tracks the acceleration command fast and smoothly. In the tracking process, aerodynamic control surfaces cooperate with reaction jets, verifying the effectiveness of the proposed approach.

Atmospheric icing problem is considered as one of the major hazards to the aviation industry and the existing anti-icing system has numerous disadvantages within it. The recent studies on the super hydrophobic surfaces inspired from lotus leaf are found to be an emerging trend in the ice protection system because of its resistance to the ice formation. But the experimental procedure for creating those surfaces is expensive and it requires specialised equipments. The work of Erbil et al. is identified to be a cost-effective and simple method for creating those surfaces based on the process called phase separation. The experimental investigation of this alternate coating method is scheduled and conducted by creating the polypropylene coating on the aluminium sheet metal. The coated aluminium surface is then tested for its ice repelling property by spraying the super-cooled liquid droplets similar to Rime ice formation. It has shown few excellent results by repelling the water and the ice formation under various atmospheric conditions. Further, the wing model and the coated layer are designed using computer software to analyse the influence of anti-icing coating on the basic stress–strain and flow properties. This novel approach provides significant cost and weight savings through a roadmap for replacing the existing ice protection systems.

Experimental investigations were carried out to study the wake characteristics of a pitching supercritical airfoil at Mach number of 0.6. Flow field inside the wake was measured by a hot-wire anemometry at downstream distances from trailing edge of 0.25 and 0.5 times the chord length. All data were taken at mean incidence angles of 0 and 3°. The amplitudes of oscillation were 1 and 3° while the oscillation frequencies were 3 and 6 Hz. Output signals acquired from sensors were analyzed besides the effects of such parameters as frequency and oscillation amplitude. Moreover, a comprehensive numerical study was carried out for the same airfoil under similar experimental test conditions; then, the results of numerical simulations were analyzed and compared with those of experimental tests. Results of the present research could be summarized as: observation of hysteresis and how it is affected by frequency and amplitude variations, observation of increasing turbulence intensity by root mean square investigation and also increasing signal energy by means of power spectral density diagram for those sensors lied inside the wake, and finally, study of correlation between wake’s interior sensors and exterior ones.

The shock waves are important phenomena in transonic turbines, which cause lots of negative effects on the aerodynamic performance. Much of attention had been paid on reducing the strength of the shock waves via modifying turbine cascade geometry, and it is highly preferred to build experiences on the relationship between the cascade aerodynamic performance and the geometric parameters. The paper presents a numerical study on the aerodynamic optimal transonic turbine cascade and its geometry characteristics. Three typical Russia transonic turbine cascades with different design conditions are selected and optimized using adjoint method at three different back pressures, respectively. Thus, the best geometry parameters for optimum aerodynamic performance can be found. Then the key geometry parameters of optimized cascades are extracted and compared with the original ones. Results show that even the best designs by hands could be less efficient than ones by computer-aided optimizations. Some experiences on how to set the key geometry parameters for a best performance are obtained. The reduced shock profiling is applied to the thermal turbomachinery and machine dynamics transonic turbine by using the adjoint method. The performance of the thermal turbomachinery and machine dynamics transonic turbine was increased significantly.

The theories of circular plates with large deflection and fracture mechanics were employed to investigate the calculating formula of stress intensity factor on prefab gap. The relationship of the opening pressure with physical dimensions of hard pulse separation device (PSD) was analyzed to achieve the feasible configuration of metal diaphragm, which could play a very important role in dual-pulse solid rocket motor. Moreover, six specific single-term tests of the metal diaphragm were conducted to validate the computing precision of designing formula. In addition, three kinds of scale experiments, e.g. the bearing test, opening test, and associated test were performed to explore the working characters of hard pulse separation device. The results indicate that the error between the experimental results and designing results is 4.4%, and the method can be applied to design the physical dimensions of metal diaphragm. The performances of bearing ability, sealability, opening and melt of PSD have been demonstrated. The results show that this kind of PSD can satisfy the requirements of dual-pulse solid rocket motor very well.

R-bar refers to the local vertical axis pointing radially upward in a satellite-fixed reference frame. Approaching a satellite along the R-bar, especially for rendezvous and docking to geostationary satellites, is advantageous in terms of safety considerations and flight time compared to other options. In this paper, a specialized study on autonomous R-bar proximity operations with respect to a geostationary target from a separation of several kilometers to a few hundreds of meters, commonly referred to as the closing phase, is carried out and a comprehensive solution for both attitude and orbit control in this scenario is proposed. An integrative design of the guidance, navigation, and control for R-bar proximity operations is presented. Impulsive R-bar hopping maneuvers are developed for the trajectory guidance. This method is shown to be passively safe and time efficient. The onboard sensors provide measurements of the line-of-sight, range to the target, attitude and angular velocity in the inertial frame. Due to the sensitivity of the sensor’s pointing in the far-range phase, a sliding mode attitude control law is introduced to align the optical axis with the line-of-sight to the target. Sensor measurements are fused and processed by an extended Kalman filter. Simulation results indicate that the proposed integrative guidance, navigation, and control algorithms are robust to uncertainties and noise, and can be used as a comprehensive solution for R-bar rendezvous and docking mission design during the closing phase.

Based on a validation of the numerical methods with an experiment, numerical simulations are carried out to study the effect of tip clearance size on the performance and tip leakage flow in a dual-stage counter-rotating axial compressor. The predicted results showed that the variation of the tip clearance size in rotor2 has a more significant impact on the overall performance and stall margin of the compressor. In addition, the impact of the tip clearance size effect is mainly on the rotor with the tip clearance size variation. The variation of the tip clearance size in rotor2 almost has no influence on the performance of rotor1, while the performance of rotor2 is increased about 1.37% at near-stall point when the tip clearance size of rotor1 is increased to 1.0 mm from 0.5 mm. At peak efficiency condition, the tip clearance size variation in rotor1 has remarkable influence on the tip leakage vortex intensity, onset point and trajectory in rotor1, but has little influence on those in rotor2. However, the tip clearance size variation in rotor2 has remarkable effect on those in both rotors. Different tip clearance size combination schemes can impact the stall-free characteristic in the counter-rotating axial compressor.

Manufacturers often develop new products by modifying and extending existing products in order to achieve new market demands while minimizing development time and manufacturing costs. In this research, an efficient derivative design process was developed to efficiently adapt existing aircraft designs according to new requirements. The proposed design process was evaluated using a case study that derives an unmanned aerial vehicle design from a baseline manned 2-seatlight sport aircraft. Multiple unmanned aerial vehicle operational scenarios were analysed to define the requirements of the derivative aircraft. These included patrol, environmental monitoring, and communications relay missions. Each mission has different requirements and therefore each resulting derivative unmanned aerial vehicle design has different geometry, devices, and performance. The derivative design process involved redefining the design requirements and identifying the minimum design variable set that needed to be considered in order to efficiently adapt the baseline design. Uncertainty was considered as well to enhance the reliability of the optimized result when it considered different conditions for each mission. An optimization method based on the possibility based design optimization was proposed to handle uncertainty that arises in the design requirements for the multi-role nature of unmanned aerial vehicles. In this paper, the possibility based design optimization method was implemented with multidisciplinary design optimization technique to derive the derivative unmanned designs based on originally manned aircraft. This approach prevented constraint violation via uncertainty variations in the operating altitude and payload weight for each. The unmanned aerial vehicle derivative designs satisfying the requirements of three different missions were derived from the proposed design process.

In the field of structural reliability, the estimation of failure probability often requires large numbers of time-consuming performance function calls. It is a great challenge to keep the number of function calls to a minimum extent. The aim of this paper is to propose an approach to assess the structural reliability in an efficient way. The proposed method could be viewed as a hybrid reliability method which combines the advantages of adaptive importance sampling, low-discrepancy sampling and artificial neural network. In the proposed method, artificial neural network is introduced to alleviate the computational burden of deterministic and boring engineering analysis, and its introduction guarantees the computational efficiency of the proposed method. While the Markov chain process is adopted to generate the experimental samples which are used to construct the artificial neural network, the introduction of Markov chain process guarantees the adaptivity of the proposed method and makes the proposed method applicable for various reliability problems. The proposed method is shown to be very efficient as the estimated failure probability is very accurate and only a small number of calls to the actual performance function are needed. The effectiveness and engineering applicability of the proposed method are demonstrated by several test examples.

In this paper, an Aircraft Research Flight Simulator equipped with Flight Dynamics Level D (highest level) was used to collect flight test data and develop new controller methodologies. The changes in the aircraft’s mass and center of gravity position are affected by the fuel burn, leading to uncertainties in the aircraft dynamics. A robust controller was designed and optimized using the H_∞ method and two different metaheuristic algorithms; in order to ensure acceptable flying qualities within the specified flight envelope despite the presence of uncertainties. The H_∞ weighting functions were optimized by using both the genetic algorithm, and the differential evolution algorithm. The differential evolution algorithm revealed high efficiency and gave excellent results in a short time with respect to the genetic algorithm. Good dynamic characteristics for the longitudinal and lateral stability control augmentation systems with a good level of flying qualities were achieved. The optimal controller was used on the Cessna Citation X aircraft linear model for several flight conditions that covered the whole aircraft’s flight envelope. The novelty of the new objective function used in this research is that it combined both time-domain performance criteria and frequency-domain robustness criterion, which led to good level aircraft flying qualities specifications. The use of this new objective function helps to reduce considerably the calculation time of both algorithms, and avoided the use of other computationally more complicated methods. The same fitness function was used in both evolutionary algorithms (differential evolution and genetic algorithm), then their results for the validation of the linear model in the flight points were compared. Finally, robustness analysis was performed to the nonlinear model by varying mass and gravity center position. New tools were developed to validate the results obtained for both linear and nonlinear aircraft models. It was concluded that very good performance of the business Cessna Citation X aircraft was achieved in this research.

The nonlinear attitude motion equations of flexible spacecraft described by the Euler angles are expressed in the vector form. Based on dynamic surface control, a new robust dynamic surface sliding mode controller is proposed for the attitude tracking and active vibration suppression of flexible spacecraft in the presence of parameter uncertainty and external disturbances. Then, a novel robust dynamic surface finite time sliding mode controller is proposed with an extended state observer such that the uncertainties can be estimated. Lyapunov stability analyses show that the two controllers can guarantee the asymptotical stability of the attitude control system. The undesirable vibration of flexible spacecraft is also actively suppressed by the modal velocity feedback approach. Finally, simulation results verified the effectiveness of the presented control algorithms.

This paper deals with the active vibration control of smart truss structure. First, the electro-mechanical coupled dynamic model of the smart structure is constructed. Then, the first-order ordinary differential equation of the control system is presented. After that, an online learning fuzzy control (OLFC) algorithm is proposed to control the structure vibrations. The OLFC algorithm is composed of a reward function, a Q learning algorithm, a rule base generator and a conventional fuzzy controller. The OLFC algorithm learns the rule base by interaction with the plant, and changes rule base generate policy via evaluative reward signal to realize the learning goal. The algorithm only needs little information about the plant to design the reward function. In order to prove the effectiveness of the proposed control algorithm, control responses are presented and compared with conventional fuzzy control method.

In this paper, fault-tolerant attitude tracking control problem is investigated for multiple spacecraft formation flying system with external disturbance, actuator saturation, and faults. A quaternion-based adaptive fault-tolerant control law is proposed based on input normalized neural network. The desired nonlinear smooth function is approximated by using input normalized neural network with an adaptive learning algorithm, and no prior knowledge about spacecraft dynamics is required. Meanwhile, in order to guarantee that the output of input normalized neural network used in the controller is bounded by the corresponding bound of the approximated unknown function, a modified adaptive law is designed to revise the sliding mode manifold. Moreover, the stability of system can be guaranteed by Lyapunov theory. Finally, the validity of the proposed control algorithm is verified through numerical simulations.

This paper develops a cooperative controller for multiple Unmanned Aerial Vehicles (UAVs) with application to target tracking. The cooperation between the UAVs is established based on an algebraic graph connection and the target information is provided externally by pinning it into a subset of the network. A backstepping-like technique is employed to design a consensus-based controller for each UAV in order to achieve target tracking in 3-D. The proposed controller computes commanded signals for the speed, flight path angle, and heading angle to track the target. The paper considers both the cases of fixed and dynamically changing communication topologies. It is shown that target tracking is achieved for fixed connection topology, if the graph has a directed spanning tree; and for the dynamically changing topology, if the union of the graphs over finite time intervals has a directed spanning tree. The system’s stability is shown using a Lyapunov function-based approach for these cases. All tracking errors are shown to be bounded as long as the target states and its derivatives up to second order are bounded. Detailed numerical simulations further illustrate the controller performance.