Lihua Gui

Simulation research of exoskeleton suit based on Neural Network Sensitivity Amplification Control

Traditional exoskeleton suit need to install many complex sensors between the pilot and the exoskeleton system to measure the human-machine interactive information, which decrease the comfort of the pilot. Sensitivity amplification control can control the exoskeleton suit to trace the pilotpsilas movement as well as need no sensors between the pilot and the exoskeleton. However, sensitivity amplification control seriously relies on the systempsilas dynamic model and it is hard to build the exoskeleton suitpsilas dynamic model exactly because the exoskeleton suit is a multi-body, multi-degree and nonlinear system. So the dynamic model of the swing leg of exoskeleton suit was identified by BP neural networks, which simplified the procedure of building the system model. Neural network sensitivity amplification control was proposed and its feasibility was validated by simulation based on Simulink and SimMechanics toolbox in Matlab.

Simulation Research of Exoskeleton Suit Based on Sensitivity Amplification Control

Exoskeleton suit is a kind of human-machine robot, which combines the humans intelligence with the powerful energy of mechanism. It can help people to carry heavy load, walking on kinds of terrains and have a broadly apply area. Though many exoskeleton suits has been developed, there need many complex sensors between the pilot and the exoskeleton system, which decrease the comfort of the pilot. Sensitivity amplification control (SAC) is a method applied in exoskeleton system without any sensors between the pilot and the exoskeleton. In this paper simulation research was made to verify the feasibility of SAC include a simple 1-dof model and a swing phase model of 3-dof. A PID controller was taken to describe the human-machine interface model. Simulation results show the human only need to exert a scale-down version torque compared with the actuator and decrease the power consumes of the pilot.

Human-machine intelligent robot system control based on study algorithm

Based on the human-machine intelligent robot system of lower extremity carrying exoskeleton, the new control method is provided, where the virtual torque control is improved. The exoskeleton model is built using SimMechanics in Matlab. The dynamics mathematics model is gotten by study the human walking to construct the controller. The controller in virtual torque control uses nonlinear direct force control while not PID control. The control law presented in this paper simplifies the controller design and not making use of any information about the operator or of any of the mechanical characteristics of the human-machine interface. The most important of this method is the mass properties need not be identified, which overcomes the maximum defect of the virtual torque control. Simulation results show the valid of the given method.

Design and Control Technique Research of Exoskeleton Suit

Naval Aeronautical Engineering Institute Exoskeleton Suit (NAEIES) is a kind of human-machine robot which combines the humans intelligence with the powerful energy of mechanism. It can help people to carry heavy load, walking on kinds of terrains. A prototype of NAEIES is proposed in this paper. When human walking, his (her) forearm has a similar motion trajectory with knee joint. So the forearm motion is measured by a potentiometer as the control signal of the knee joint. The hip joint motion is realized by a gas spring. This is the simplest method to realize the motion of NAEIES. The principle of the method was illustrate in the paper and for the further study a control techniques based on the feedback of angle acceleration is proposed and simulated with the one-Dof and two-Dof model of NAEIES leg.

Model of Exoskeleton Suit

To facilitate the analysis of the characteristics of the exoskeleton suit system, assume that every link of the exoskeleton suit is rigid connecting rod, and the connecting rods are connected through joints to form a multi-rigid-body chain structure.

Force Control of Exoskeleton Suit Based on Inner Position Loop

The robot’s explicit force control can be divided into two kinds: the explicit force control based on the position and the explicit force control based on the force [1, 2]. The structure of the explicit force control based on the force is same as that of the direct force control described in the previous chapter, and this chapter will introduce the explicit force control method based on the position.

Impedance Control of Exoskeleton Suit with Uncertainties

The exoskeleton suit is a very complex multiple-input–multiple-output system with time-varying, strong coupling, and nonlinear dynamical characteristics. Because of the inaccurate measurement and modeling, the change of the load, and the influence of external disturbance, actually the accurate complete motion model of the exoskeleton suit cannot be obtained, which is so-called uncertainty.

Sensitivity Amplification Control of Exoskeleton Suit

The exoskeleton suit combines the advantages of the human intelligence provided by the operator and of the mechanical energy provided by the exoskeleton suit. That is to say, the operator provides the intelligent control system for the exoskeleton suit, and the exoskeleton suit provides most of the energy needed for walking.

Exoskeleton Suit’s Reference Trajectory Estimated Method Based on Neural Network

In Chap. 6, we use human–machine interaction model to estimate the reference trajectory, reference speed, and reference acceleration of the exoskeleton suit, but the precise form of human–machine acting force model cannot be known in advance; the use of the fixed human–machine acting force model cannot estimate the intention of the human accurately (i.e., the reference trajectory of the exoskeleton suit); for example, in different motion states, the forms and parameters of the human–machine acting force are different (linear or nonlinear or order).

Impedance Control of Exoskeleton Suit

Impedance control is also one of the classical force control methods. It is according to the relationship between position of the machine end (or velocity) and the acting force of the end part, and by adjusting feedback position error, velocity error or stiffness to achieve the purpose of control force.