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In this paper, the linear parameter varying (LPV) reliable non-fragile control for the hypersonic vehicle (HV) is studied in case of disturbance and controller gain variations. Due to the dramatic and complex change of the HV longitudinal dynamics, a polytopic LPV model is constructed for the HV system stability analysis and controller design in a large flight envelope. Then, a disturbance observer (DOB)-based non-fragile controller for HV system with disturbance and unknown controller uncertainty is designed to guarantee the closed-loop stability and control performance under an adequate level of reliability, which is formed with two parts. One part is a DOB to compensate the uncertain dynamics and disturbance. The other is a robust non-fragile controller, which is designed based on a novel robust reliability method to deal with controller uncertainties, and obtained by carrying out reliability-based linear matrix inequality optimization. The presented controller for HV can provide the robustness as well as an excellent performance under the condition that the prescribed reliability degree is satisfied. Finally, numerical simulation for an HV demonstrates the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Summary: The solid rocket booster is widely used in the launch mission for hypersonic vehicles nowadays, whose ascent energy management is still a challenging problem due to the inherent dynamic nonlinearity. This paper casts the problem into an equivalent ascent guidance one and proposes a model predictive static programming (MPSP) based solution. The MPSP‐based method is a computationally efficient solver that adapts to different energy demands while guaranteeing the satisfaction of terminal constraints. To further improve the performance of MPSP in this problem, a Bézier spline guidance method is proposed to generate high‐quality reference trajectories such that the MPSP can converge with high accuracy while satisfying the real‐time requirement. Additionally, an online parameter estimation based on the extended Kalman filter is employed to avoid large terminal state deviations incurred by parametric uncertainties during the Bézier curve computation and linearization in MPSP. Numerical simulations with different hard terminal constraints and uncertainties are conducted to demonstrate the effectiveness and robustness of the proposed algorithm. The simulation results show that our proposed algorithm can guide the hypersonic vehicle to a given terminal state under uncertainties and outperforms several existing ascent energy management methods. [ABSTRACT FROM AUTHOR]

Generation of optimal reentry trajectory for a hypersonic vehicle (HV) satisfying both boundary conditions and path constraints is a challenging task. As a relatively new swarm intelligent algorithm, an adaptive fireworks algorithm (AFWA) has exhibited promising performance on some optimization problems. However, with respect to the optimal reentry trajectory generation under constraints, the AFWA may fall into local optimum, since the individuals including fireworks and sparks are not well informed by the whole swarm. In this paper, we propose an improved AFWA to generate the optimal reentry trajectory under constraints. First, via the Chebyshev polynomial interpolation, the trajectory optimization problem with infinite dimensions is transformed to a nonlinear programming problem (NLP) with finite dimension, and the scope of angle of attack (AOA) is obtained by path constraints to reduce the difficulty of the optimization. To solve the problem, an improved AFWA with a new mutation strategy is developed, where the fireworks can learn from more individuals by the new mutation operator. This strategy significantly enhances the interactions between the fireworks and sparks and thus increases the diversity of population and improves the global search capability. Besides, a constraint-handling technique based on an adaptive penalty function and distance measure is developed to deal with multiple constraints. The numerical simulations of two reentry scenarios for HV demonstrate the validity and effectiveness of the proposed improved AFWA optimization method, when compared with other optimization methods. [ABSTRACT FROM AUTHOR]

The objective of this paper is to investigate an online method to generate an optimal ascent trajectory for air-breathing hypersonic vehicles. A direct method called the Pseudo-spectral method shows promise for real-time optimal guidance. A significant barrier to this optimisation-based control strategy is computational delay, especially when the solution time of the non-linear programming problem exceeds the sampling time. Therefore, an online guidance algorithm for an air-breathing hypersonic vehicles with process constraints and terminal states constraints is proposed based on the Pseudo-spectral method and sensitivity analysis in this paper, which can reduce online computational costs and improve performance significantly. The proposed ascent optimal guidance method can successively generate online open-loop suboptimal controls without the design procedure of an inner-loop feedback controller. Considering model parameters' uncertainties and external disturbance, a sampling theorem is proposed that indicates the effect of the Lipschitz constant of the dynamics on sampling frequency. The simulation results indicate that the proposed method offers improved performance and has promising ability to generate an optimal ascent trajectory for air-breathing hypersonic vehicles. [ABSTRACT FROM AUTHOR]

In this paper, an active fault-tolerant control (AFTC) method with adaptive gain is proposed for spacecrafts which subject to model uncertainty, external disturbance and actuator fault. A novel adaptive-gain finite-time observer is designed to solely estimate fault in the presence of disturbance for fault diagnosis. By incorporating the dual-layer gain adaption scheme into the nonlinear integral sliding mode control (ISMC), a reconfigurable controller is designed to accommodate fault. Due to the reaching phase elimination of ISMC, the gain tracking to the unknown bounded disturbance can be accelerated while it is maintained that the control gain will not be overestimated and the bound knowledge of fault/disturbance is not required. Simulation results verify the effectiveness and improvement of the proposed FTC method. [ABSTRACT FROM AUTHOR]

In this study, hypersonic vehicle (HV) tracking control in the presence of uncertainties and external disturbance is investigated. As the exact bounds of uncertainties and disturbances are usually unknown during flight, a disturbance observer (DOB)-based gain adaptation high-order sliding mode control (HOSMC) method is proposed for HVs. To mitigate the chattering effect while maintaining strong robustness, a method combining the advantages of the DOB and gain adaptation is introduced into the HOSMC. The DOB is employed to estimate and reject the uncertainties and external disturbance. Additionally, an adaptive control law is developed to compensate for estimation errors. By combining the DOB and the adaptive HOSMC, the unnecessarily large gain for maintaining robustness is reduced; thus, the chattering is mitigated. The effectiveness of the proposed control method is validated via simulation, in which a strong robustness, high tracking performance, and reduced chattering effect are achieved under uncertainties and external disturbance. [ABSTRACT FROM AUTHOR]

This paper proposes an active fault-tolerant control (AFTC) system for spacecrafts subject to model uncertainty, external disturbance and actuator fault simultaneously. Fault diagnosis is implemented by a robust fault observer with a simple structure. The observer can separately estimate the fault in the existence of disturbance and uncertainty. The influence on observation performance from disturbance and uncertainty is attenuated by linear matrix inequality (LMI) optimization. For the fault-tolerant controller, asymmetric barrier Lyapunov function and backstepping method are used to constrain all the states. Meanwhile, the control input is restricted by a saturation function. Validation and comparative simulations are implemented to demonstrate the proposed AFTC method. [ABSTRACT FROM AUTHOR]

An online adaptive dynamic programming (ADP) attitude-tracking controller based on policy iteration is proposed, aiming to approach the optimal control of hypersonic vehicles (HVs). The Bellman equation, known as the principal recursive dynamic programming formula, is provided to obtain the controller. In particular, the control action is generated by the ADP controller to track the attitude trajectory. In order to approach optimal control in the uncertain nonlinear HVs system, we use policy iteration to approximate the Bellman equation and build an actor-predictor-critic framework, in which the action network, state estimator and critic network are adopted to implement the policy iteration. Meanwhile, an offline learning method is provided to approach the initial value of iterative computations and improve the efficiency of online learning. The comparative simulations demonstrate the good performance of PIADP with aerodynamic parameter perturbations and random disturbances. [ABSTRACT FROM AUTHOR]