In this paper, an adaptive neural output-constrained control algorithm is proposed for a class of non-affine kinetic kill vehicle (KKV) systems. The key point is that the non-affine control law can be designed and the output of the KKV system conform to the output limit with the aid of the proposed method. Due to the aerodynamic moments, the actual control torque is non-affine, which can be addressed by introducing an integral process to the design of the controller. Besides, in order to improve the control precision, a nonlinear mapping is put forward so that the output constraint can be transformed to the constraint of the introduced dynamic signal that can be simply achieved. From the simulation results it can be concluded that the states of the KKV system can track the desired trajectories in spite of different working conditions and the control precision is higher compared with other control methods.

This paper studied the back-stepping adaptive sliding mode control (SMC) attitude problem of quaternion aircraft model based on radial basis function (RBF) network approximation. Firstly, a sliding mode controller is designed based on the back-stepping method (BSM) for the nonlinear aircraft model. Secondly, a RBF network algorithm is designed to compensate for the unknown and uncertain parts of the aircraft system. RBF network has simple network structure and good generalisation ability, avoids lengthy and unnecessary calculations, realises adaptive approximation of unknown parts in the aircraft model, and through the adjustment of adaptive weights, the convergence and stability of the entire closed-loop system (CLS) are guaranteed. Finally, the anti-interference performance of the controller is verified by simulation of the actuator fault model. Our proposed method has all-right control performance indicated by the simulation results.

This paper considers the problem of a three-axis flexible satellite attitude stabilisation subject to the vibration of flexible appendages and external environmental disturbances, which affect the rigid body motion. To solve this problem, a disturbance observer is proposed to estimate and thereby reject the flexible appendage vibration. Based on the H∞ and Linear Matrix Inequality (LMI) approach, a controller for spacecraft with flexible appendages is proposed to ensure robustness as well as attitude stability with high precision. Stability analysis of the overall closed-loop system is provided via the Lyapunov method. The simulation results of three-axis flexible spacecraft demonstrate the robustness and effectiveness of the proposed method.

Stratospheric airships are lighter-than-air vehicles that work at an altitude of 20km in the lower calm portion of the stratosphere. They can be used as real-time surveillance platforms for environment monitoring and civil communication. Solar energy is the ideal power choice for long-endurance stratospheric airships. Attitude control is important for airships so that they can point at a target for observation or adjust the attitude to improve the output performance of solar panels. Stratospheric airships have a large volume and semi-flexible structure. The typical actuators used are aerodynamic surfaces, vectored thrust and ballonets. However, not all these actuators can work well under special working conditions, such as low density and low speed. In this study, moving-mass control is introduced to stratospheric airships because its control efficiency is independent of airspeed and atmospheric density. A nonlinear feedback controller based on generalised inverse with a nonlinear mapping module is designed to implement moving-mass control. Such a new station keeping scheme with moving masses is proposed for airships with different working situations.

A Jacobian-based algorithm that is useful for planning the motion of a floating rigid body operated using two input torques is addressed in this paper. The rigid body undergoes a four-rotation fully reversed (FR) sequence of rotations which consists of two initial rotations about the axes of a coordinate frame attached to the body and two subsequent rotations that undo the preceding rotations. Although a Jacobian-based algorithm has been useful in exploring the inverse kinematics of conventional robot manipulators, it is not apparent how a correct FR sequence for a desired orientation could be found because the Jacobian of FR sequences is singular as well as being a null matrix at the identity. To discover the FR sequences that can synthesize the desired orientation circumventing these difficulties, the Jacobian algorithm is reformulated and implemented from arbitrary orientations where the Jacobian is not singular. Due to the insufficient degrees-of-freedom of four-rotation FR sequences required to achieve all possible orientations, the rigid body cannot achieve certain orientations in the configuration space. To best approximate these infeasible orientations, the Jacobian-based algorithm is implemented in the sense of least squares. As some orientations can never be attained by a single four-rotation FR sequence, two different four-rotation FR sequences are exploited alternately to ensure the convergence of the proposed algorithm. Assuming the orientation is supposed to be manipulated using three input torques, the switching Jacobian algorithm proposed in this paper has significant practical importance in planning paths for aerospace and underwater vehicles which are maneuvered using only two input torques due to the failure of one of the torque-generation mechanisms.

The aim of this article is to present algorithms to compute the firstconjugate time along a smooth extremal curve, where the trajectoryceases to be optimal. It is based on recent theoretical developmentsof geometric optimal control, and the article contains a reviewof second order optimality conditions.The computations are related to a testof positivity of the intrinsic second order derivative or a test ofsingularity of the extremal flow. We derive an algorithm called COTCOT(Conditions of Order Two and COnjugate Times), available on the web,and apply it to the minimal time problem of orbit transfer, and to theattitude control problem of a rigid spacecraft.This algorithm involves both normal and abnormal cases.

In this paper, we propose a model-based control system design for autonomous flight and guidance control of a small-scale unmanned helicopter. Small-scale unmanned helicopters have been studied by way of fuzzy and neural network theory, but control that is not based on a model fails to yield good stabilization performance. For this reason, we design a mathematical model and a model-based controller for a small-scale unmanned helicopter system. In order to realize a fully autonomous small-scale unmanned helicopter, we have designed a MIMO attitude controller and a trajectory controller equipped with a Kalman filter-based LQI for a small-scale unmanned helicopter. The design of the trajectory controller takes into consideration the characteristics of attitude closed-loop dynamics. Simulations and experiments have shown that the proposed scheme for attitude control and position control is very useful.