Input torque sensitivity to uncertain parameters in biped robot

Input torque is the main power to maintain bipedal walking of robot, and can be calculated from trajectory planning and dynamic modeling on biped robot. During bipedal walking, the input torque is usually required to be adjusted due to some uncertain parameters arising from objective or subjective factors in the dynamical model to maintain the pre-planned stable trajectory. Here, a planar 5-link biped robot is used as an illustrating example to investigate the effects of uncertain parameters on the input torques. Kine-matic equations of the biped robot are firstly established by the third-order spline curves based on the trajectory planning method, and the dynamic modeling is accomplished by taking both the certain and uncertain parameters into account. Next, several evaluation indices on input torques are intro-duced to perform sensitivity analysis of the input torque with respect to the uncertain parameters. Finally, based on the Monte Carlo simulation, the values of evaluation indices on input torques are presented, from which all the robot param-eters are classified into three categories, i.e., strongly sensi-tive, sensitive and almost insensitive parameters.

Robust optimization of aircraft weapon delivery trajectory using probability collectives and meta-modeling

Conventional trajectory optimization techniques have been challenged by their inability to handle threats with irregular shapes and the tendency to be sensitive to control variations of aircraft. Aiming to overcome these difficulties, this paper presents an alternative approach for trajectory optimization, where the problem is formulated into a parametric optimization of the maneuver variables under a tactics template framework. To reduce the size of the problem, global sensitivity analysis （GSA） is performed to identify the less-influential maneuver variables. The probability collectives （PC） algorithm, which is well-suited to discrete and discontinuous optimization, is applied to solve the trajectory optimization problem. The robustness of the trajectory is assessed through multiple sampling around the chosen values of the maneuver variables. Meta-models based on radius basis function （RBF） are created for evaluations of the means and deviations of the problem objectives and constraints. To guarantee the approximation accuracy, the meta-models are adaptively updated during optimization. The proposed approach is demonstrated on a typical airground attack mission scenario. Results reveal that the proposed approach is capable of generating robust and optimal trajectories with both accuracy and efficiency.

Ski-jump trajectory based on take-off velocity

The theoretical method estimating ski-jump trajectory was paid attention to and modified. The present method is based on the effects of the take-off velocity and the angle in the sensitivity analysis of parameters. The experiments are conducted for a triangular-shaped flip bucket in order to reveal the relationships between the take-off velocity and its influencing factors. The results show that, the take-off velocity has a much larger effect on the impact point than the take-off angle. The take-off velocities of both upper and lower trajectories are all functions of the approach flow Froude number, the deflector height and the deflection angle, especially, the results of the deflection angle of 25° could be directly used when this angle is larger than 25° Meanwhile, this method is checked and the maximum relative errors of both U calx and L_（calx） are 5.1% and 5.6%, respectively.

Comprehensive modeling and parameter identification of wind farms based on wide-area measurement systems

With intermittence and stochastics of wind power largely introduced into power systems, power system stability analysis and control is in urgent need of reliable wind farm models. Considering the superiority of wide-area measurement systems, this paper develops a novel methodology for practical synchrophasor measurement-based modeling and parameter identification of wind farms. For the sake of preserving basic structural characteristics and control patterns simultaneously, a comprehensive wind farm model is constructed elaborately. To improve the efficiency of the identification procedure,dominant parameters are classified and selected by trajectory sensitivity analysis. Furthermore, an improved genetic algorithm is proposed to strengthen the capability of global optimization. The test results on the WECC benchmark system and the CEPRI 36-bus system demonstrate the effectiveness and reliability of the proposed modeling and identification methodology.

Hierarchical parameter estimation of DFIG and drive train system in a wind turbine generator

A new hierarchical parameter estimation method for doubly fed induction generator （DFIG） and drive train system in a wind turbine generator （WTG） is proposed in this paper. Firstly, the parameters of the DFIG and the drive train are estimated locally under different types of disturbances. Secondly, a coordination estimation method is further applied to identify the parameters of the DFIG and the drive train simultaneously with the purpose of attaining the global optimal estimation results. The main benefit of the proposed scheme is the improved estimation accuracy. Estimation results confirm the applicability of the proposed estimation technique.

Online Decision-Making and Control of Power System Stability Based on Super-Real-Time Simulation

During power grid cascading failure,the operating point changes frequently,resulting in a mismatch or inaccuracy of online pre-decision making emergency control strategy.To solve this problem,an online power system stability decisionmaking and control method based on super-real-time simulation is presented in this paper.A decision-making and control system is developed in which the three main operation modes,offline pre-decision-making,online pre-decision-making,and real-time control,are all coordinated.To verify the method,ADPSS(advanced digital power system simulator)is used to simulate a digital power grid with about 20,000 buses.The closed-loop operation of the digital power grid and the online decisionmaking and control system are implemented.Test results show that when online pre-decision making control strategies are mismatched,aided real-time control works well and can prevent power grid stability loss.