The deceleration effect of the deployable aerodynamic decelerator is not as good as a parachute in the subsonic region. This paper proposes a novel concept of using a parachute-like configuration (PLC) to enhance the deceleration performance of the mechanically deployable aerodynamic decelerator (MDAD) through structural transformation. The MDAD turned into the PLC from the sphere cone configuration (SCC) at Ma 0.8. The aerodynamic characteristics of the two configurations are analysed deeply. Compared to the SCC, the results show that the drag coefficient increases effectively, and the maximum increases is about 10% in the PLC. The airflow is altered by the MDAD configuration, which can affect the surface pressure and temperature. During the transformation process, the axial and normal force coefficients tend to stabilise. However, the static stability of the PLC deteriorates sharply compared to the SCC when the angle-of-attack exceeds 45°.

This paper presents an integrated guidance and control (IGC) design method for an unmanned aerial vehicle with static stability which is described by a nonlinear six-degree-of-freedom (6-DOF) model. The model is linearized by using small disturbance linearization. The dynamic characteristics of pitching mode, rolling mode and Dutch rolling mode are obtained by analysing the linearized model. Furthermore, an IGC design procedure is also proposed in conjunction with a proportional–integral–derivative (PID) control method and fuzzy control method. A PID controller is applied in the control loop of the elevator and aileron, and the attitude angle and attitude angular velocity are used as compensation feedback, giving a simple and low-order control law. A fuzzy control method is applied to perform the cross-coupling control of rolling and yawing. Finally, the 6-DOF simulation shows the effectiveness of the developed method.

Several static and dynamic stability criteria have been defined in the course of walking-robot history. Nevertheless, previous work on the classification of stability criteria for statically stable walking machines (having at least four legs) reveals that there is no stability margin that accurately predicts robot stability when inertial and manipulation effects are significant. In such cases, every momentum-based stability margin fails. The use of an unsuitable stability criterion yields unavoidable errors in the control of walking robots. Moreover, inertial and manipulation effects usually appear in the motion of these robots when they are used for services or industrial applications. A new stability margin that accurately measures robot stability considering dynamic effects arising during motion is proposed in this paper. The new stability margin is proven to be the only exact stability margin when robot dynamics and manipulation forces exist. Numerical comparison has been conducted to support the margin's suitability. Stability-level curves are also presented on the basis of a suitable stability margin to control the trajectory of the center of gravity during the support phase.

Several static and dynamic stability criteria have been defined in the course of walking robot history. Nevertheless, different applications may require different stability criteria and, to the authors' best knowledge, there is no qualitative classification of such stability measurements. Using the wrong stability criterion to control a robot gait may prevent the task from succeeding. Furthermore, if the optimum criterion is found, the robot gait can also be optimized. In this paper, the stability criteria that have been applied to walking robots with at least four legs are examined in terms of their stability margins in different static and dynamic situations. As a result, a qualitative classification of stability criteria for walking machines is proposed so that the proper criterion can be chosen for every desired application.

This paper describes a new method for generating the turning-gait of a six-legged robot using a combined genetic algorithm (GA)-Fuzzy approach. The main drawback of the traditional methods of gait generation is their high computational load. Thus, there is still a need for the development of a computationally tractable algorithm that can be implemented online to generate stable gait of a multilegged robot. In the proposed genetic-fuzzy system, the fuzzy logic controllers (FLCs) are used to generate the stable gait of a hexapod and a GA is used to improve the performance of the FLCs. The effectiveness of the proposed algorithm is tested on a number of turning-gait generation problems of a hexapod that involve translation as well as rotation of the vehicle. The hexapod will have to take a sharp circular turn (either clockwise or counter-clockwise) with minimum number of ground legs having the maximum average kinematic margin. Moreover, the stability margin should lie within a certain range to ensure static stability of the vehicle. Each leg of a six-legged robot is controlled by a separate FLC and the performance of the controllers is improved by using a GA. It is to be noted that the actual optimization is done off-line and the hexapod can use these optimized FLCs to navigate in real-world scenarios. As an FLC is computationally less expensive, the proposed algorithm will be faster compared with the traditional methods of gait-generation, which include both graphical as well as analytical methods. The GA-tuned FLCs are found to perform better than the author-defined FLCs.