Research and Application of 40 kW Electric Servo System on Gravity-1 Launch Vehicle

This article introduces the 40 kW electric servo system used by Gravity-1 strap-on launch vehicle, which mainly includes the composition, function and related equipment of the system. Aiming at the measurement deviation caused by the closed loop of resolver, a compensation algorithm is designed;aiming at the monitoring of the output power of the thermal battery, an algorithm without sensory monitoring the bus current is designed. In the end, the effectiveness of the two algorithms was verified by testing.

Wave Heave Compensation Based on An Optimized Backstepping Control Method

The vessel heave motion caused by wave action increases the difficulty of installing offshore wind equipment.On-board wave heave compensation devices have therefore become increasingly critical in ensuring the stability and safety of the gangway and working platform.This study accordingly improves the compensation effect of such devices by developing a wave heave compensation model and designing an optimized backstepping control method.First,a model of the compensation system including the servo motor and electric cylinder is established by using the mechanism method.Second,a backstepping control method is designed to track the vessel heave motion,and particle swarm optimization is applied to optimize the control parameters.Finally,MATLAB/Simulink is used to simulate the application of the optimized backstepping controller,then regular and irregular heave motions are applied as input to a Stewart platform to evaluate the effectiveness of the control method.The experimental results show that the compensation efficiency provided by the proposed optimized backstepping control method is larger than 75.0%.

大功率高电压电动伺服系统在运载火箭上的应用研究

The 30 kW high-power electric servo system used in the solid booster of the Long March 6 A(LM-6 A)launch vehicle is introduced,and the function,composition of the system as well as its constituent equipments are detailed.To solve the problem of out-of-tolerance in the system dynamic characteristics,an advanced correction network algorithm architecture and double notch filter were designed.Experimental verification was conducted to prove that the dynamic characteristics requirement under multiple operating conditions could be met.

Adaptive Fuzzy Torque Control of Passive Torque Servo Systems Based on Small Gain Theorem and Input-to-state Stability

Passive torque servo system （PTSS） simulates aerodynamic load and exerts the load on actuation system, but PTSS endures position coupling disturbance from active motion of actuation system, and this inherent disturbance is called extra torque. The most important issue for PTSS controller design is how to eliminate the influence of extra torque. Using backstepping technique, adaptive fuzzy torque control （AFTC） algorithm is proposed for PTSS in this paper, which reflects the essential characteristics of PTSS and guarantees transient tracking performance as well as final tracking accuracy. Takagi-Sugeno （T-S） fuzzy logic system is utilized to compensate parametric uncertainties and unstructured uncertainties. The output velocity of actuator identified model is introduced into AFTC aiming to eliminate extra torque. The closed-loop stability is studied using small gain theorem and the control system is proved to be semiglobally uniformly ultimately bounded. The proposed AFTC algorithm is applied to an electric load simulator （ELS）, and the comparative experimental results indicate that AFTC controller is effective for PTSS.

A concurrent optimization approach for energy efficient multiple axis positioning tasks

Automated production systems typically comprise numerous electrical servo drives,many of which conduct positioning motions,e.g.for handling or manipulation tasks.The power electronics of modern multi-axis systems often comprise coupled DC-links,enabling for internal exchange of recuperative brake energy.However,the motion sequences of manipulators are often commanded at maximum dynamics for minimum time motion,neglecting possible optimization potential,e.g.available idle time,leading to inefficient energy management.A robust trajectory optimization approach based on the particle swarm algorithm and well-established path planning methods is presented for the adaption of multi-axis positioning tasks with only two parameters per axis and positioning motion during system run-time.Experimental results prove that,depending on the positioning task and chosen optimization constraints,energy demands are distinctly reduced.The approach is applicable to diverse multi-axis configurations and enables for considerable energy savings without additional hardware invest.