This paper designs a high-performance adaptive controller for the uncertain model of hypersonic flight vehicles (HFVs) proceed by faulty and hysteretic actuators. A parameterized HFV model is derived, based on which adaptive tracking controllers for velocity and altitude are designed, sequentially. Compared with other adaptive strategies that mainly focus on the parametric uncertainty and asymptotic tracking, the utilization of prescribed performance control technique can largely improve the transient characteristics of HFVs. A novel handling on angleof- attack (AOA) is proposed with the help of barrier functions. As a result, the magnitude of AOA is limited to match the requirement of the scramjet. Partial loss of effectiveness (PLOE) of actuators is also taken into account, while the backlash hysteresis in aerodynamic control surfaces is accommodated by an adaptive inverse compensation. Corresponding analysis shows that both the limited AOA and the desired performance can be guaranteed despite PLOE of actuators. A simulation study is provided to verify the effectiveness of the proposed controller.

This article deals with the problem of mobile robot path planning in an unknown environment that contains both static and dynamic obstacles, utilizing a reinforcement learning approach. We propose an improved Dyna- ${Q}$ algorithm, which incorporates heuristic search strategies, simulated annealing mechanism, and reactive navigation principle into ${Q}$ -learning based on the Dyna architecture. A novel action-selection strategy combining $\varepsilon $ -greedy policy with the cooling schedule control is presented, which, together with the heuristic reward function and heuristic actions, can tackle the exploration-exploitation dilemma and enhance the performance of global searching, convergence property, and learning efficiency for path planning. The proposed method is superior to the classical ${Q}$ -learning and Dyna- ${Q}$ algorithms in an unknown static environment, and it is successfully applied to an uncertain environment with multiple dynamic obstacles in simulations. Further, practical experiments are conducted by integrating MATLAB and robot operating system (ROS) on a physical robot platform, and the mobile robot manages to find a collision-free path, thus fulfilling autonomous navigation tasks in the real world.

When working at extremely high altitude, aerodynamic surfaces of air-breathing hypersonic vehicles (AHVs) may not provide sufficient control authority. To remedy this shortage, we consider AHVs equipped with the auxiliary reaction control system (RCS), which utilize a suite of control jets to compensate for ineffective aerodynamic surfaces. A novel longitudinal compound control is proposed to generate commands of aerodynamic surfaces and RCS, adaptively. Constrained angleof- attack, uncertain parameters, and flexible dynamics are also considered.