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Variable Impedance Control for Bipedal Robot Standing Balance Based on Artificial Muscle Activation Model
Variable Impedance Control for Bipedal Robot Standing Balance Based on Artificial Muscle...
Yin, Kaiyang;Xue, Yaxu;Yu, Yadong;Xie, Shuangxi
Hindawi Journal of Robotics Volume 2021, Article ID 8142161, 9 pages https://doi.org/10.1155/2021/8142161 Research Article Variable Impedance Control for Bipedal Robot Standing Balance Based on Artificial Muscle Activation Model Kaiyang Yin , Yaxu Xue , Yadong Yu , and Shuangxi Xie School of Electrical and Mechanical Engineering, Pingdingshan University, Pingdingshan 467000, China Correspondence should be addressed to Yaxu Xue; firstname.lastname@example.org Received 13 April 2021; Accepted 23 June 2021; Published 2 July 2021 Academic Editor: Gordon R. Pennock Copyright © 2021 Kaiyang Yin et al. *is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. *e bipedal robot should be able to maintain standing balance even in the presence of disturbing forces. *e control schemes of bipedal robot are conventionally developed based on system models or ﬁxed torque-ankle states, which often lack robustness. In this paper, a variable impedance control based on artiﬁcial muscle activation is investigated for bipedal robotic standing balance to address this limitation. *e robustness was improved by applying the artiﬁcial muscle activation model to adjust the impedance parameters. In particular, an ankle variable impedance model was used to obtain the antidisturbance torque which combined with the ankle dynamic torque to estimate the desired ankle torque for robotic standing balance. *e simulation and prototype experimentation results demonstrate that the control method improves the robustness of bipedal robotic standing balance control. complete the bipedal robotic standing balance control [5, 6], 1. Introduction and this approach relies on the robotic dynamic model Nowadays, a vast variety of bipedal robots have been created which is diﬃcult to improve the robustness of the standing to help humans and they have been applied to a myriad of balance control. With the development of intelligent control social applications, such as military training, medical ser- algorithms which are increasingly being used to solve the vices, industrial manufacturing, and other ﬁelds . In these robotic standing balance control problems , the intelli- applications, the working environments are usually un- gent control algorithms rely on a large amount of test data. known, which have the risk to interfere with the standing In addition, robots have some hardware limits. For example, balance of the bipedal robots. How to prevent robots from the input saturation and actuator dead zones aﬀect the falling, that is, standing balance control, is a fundamental control robustness, and the intelligent algorithms and control problem for bipedal robots. *e ankle plays an adaptive methods provide eﬀective solutions [8, 9]. important role in bipedal robotic standing balance control *e bipedal robots have a complex structure, with the , which raises concerns for robotic ankle control. characteristics of system nonlinearity and structural vari- Researchers have done a lot of works on bipedal robotic ability, which brings about great challenges to motion standing balance control. Vukobratovic et al.  referred to control . *rough a long period of evolution, human the principle of mechanical arm balance control and pro- beings have the ability to adapt and swiftly respond to posed the Zero Moment Point (ZMP) control method which environmental changes. *ese abilities of human beings adjusts the joint torque according to the trajectory of real- have provided the best guidance to advance the design of time ZMP. However, the ZMP control method has some robotic controllers. *e authors in  attempted to build limitations: the ZMP was calculated by sensor information the virtual neuromuscular model for robotic control. *is feedback which lags behind the actual attitude change, and approach can generate human-like diverse and robust lo- the delay will cause the controller ring . According to the comotion behaviors. However, the major components of this law of conservation of momentum, some scholars simul- control strategy are twofold: the virtual muscle model and taneously adjust the angular and linear momentum to the muscle activation model. However, the virtual model 2 Journal of Robotics involves many control model parameter sets, such as virtual the impedance model which is based on the robotic ankle muscular parameters, which limit the general applicability of and its change rate output the disturbance torque (τ ). From this approach . this, the ankle desired torque (τ ) for bipedal robotic To make robotic joints present a “gloppy” or “springy” standing balance control is aggregated output of τ and τ . r e compliant control behavior similar to human joints, the concept of impedance control in the ﬁeld of robots has been 2.2. Dynamic Torque Estimation. *e dynamic model de- proposed by Hogan . Impedance control is extensively scribes the relationship between the motion of the bipedal employed in robotic control and its robustness and feasi- robot and the dynamic torque (τ ) of the robotic joint. In bility have been acknowledged by many research studies order to study the bipedal robotic standing balance ankle [14, 15]. However, a ﬁxed impedance model may not suﬃce strategy, the complex actions such as arm swing, curved in many applications, and variable impedance is necessary to body, and step can be ignored. Without loss of generality, the achieve optimal performance of the system ; for ex- bipedal robot was simpliﬁed as an inverted pendulum model ample, human beings have the ability to adjust their joint with swinging around the ankle, in this paper, and all the impedance through muscle contraction. robotic weight is concentrated on the center of mass (CoM). In this paper, the robotic ankle is streamlined into an *e robotic ankle in the initial state is marked as the co- impedance model, and an artiﬁcial muscle activation model ordinate origin, and the horizontal and vertical directions is built to adjust the impedance parameters. *en, the are marked as the x-axis and y-axis, respectively. *e bipedal variable impedance control based on artiﬁcial muscle acti- robotic inverted pendulum model is illustrated in Figure 2. vation for bipedal robot balance was proposed. Speciﬁcally, Based on the established x-y coordinate system, the the ankle antidisturbance torque is obtained by constructing diﬀerential equation of the robotic torso rotating around the the ankle variable impedance model, and the ankle dynamic ankle can be expressed as torque is calculated by constructing an inverted pendulum model of the bipedal robot. By combination of anti- F l sin θ − F l cos θ � τ . (1) y x r disturbance torque and dynamic torque, the expected ankle torque for standing balance control is estimated. *e main *e robotic CoM horizontal force (F ) can be expressed contributions of this work are threefold: (1) it proposes a as variable impedance control for bipedal robot standing balance, (2) it develops an impedance parameter sets update (2) F � m (l sin θ), approach based on artiﬁcial muscle activation, and (3) the dt proposed work was validated and evaluated by both sim- that is, ulation and prototype experimentation approach. € _ F � mlθcos θ − θ sin θ. (3) 2. Methods *e robotic CoM vertical force (F ) can be described as *e proposed variable impedance control method is used to estimate the ankle desired torque (τ ) for bipedal robotic (4) F � mg + m (l cos θ), standing balance control. Accordingly, the proposed vari- dt able impedance control method is composed of three vital that is, components: a dynamic model to estimate the dynamic torque (τ ), an ankle impedance model to calculate the 2 € _ F � mg − ml θsin θ + θ cos θ . (5) disturbance torque (τ ), and an impedance adjust compo- nent to update the impedance parameters based on artiﬁcial According to equations (1), (3), and (5), the bipedal muscle activation model. robotic standing balance ankle dynamic model can be de- scribed as 2.1. Control Method Overview. *e framework of the pro- (6) τ � Iθ − mglsin θ, posed variable impedance control for bipedal robot standing balance is illustrated in Figure 1, with the vehicle platform acceleration and deceleration in this work to simulate where I represents the rotational inertia, and I �ml . various perturbations of a bipedal robot standing balance. *ere are two control loops in parallel, with the dynamic model and the impedance model being the main compo- 2.3. Disturbance Torque Estimation. *e impedance model nents of the two loops. *e inputs of the dynamic model are refers to the dynamic relationship between the input ﬂow the robotic ankle angle and its change rate [θ θ ], and and the output eﬀort at the interaction port between a foot foot the output is the dynamic torque (τ ). Likewise, the inputs of manipulator and its environment . *is paper regarded the impedance adjust component are the same as those of the the robotic ankle joint as an impedance model and used it to dynamic model. *e model ﬁrst calculates the muscle ac- estimate the ankle disturbance torque. *e bipedal robotic tivation (a) based on the artiﬁcial muscle activation model ankle impedance model’s schematic diagram is shown in and, subject to the parameters update operation, inputs to Figure 3. Journal of Robotics 3 External θ θ foot foot disturbance Bipedal robot Muscle activation Parameter update Impedance adjust component K B M Impedance model Dynamic model τ τ q r Ankle torque actuator The hardware The control system Figure 1: *e framework of variable impedance control for bipedal robot standing balance control. Equilibrium Robotic CoM position torso foot mg foot BK Figure 3: *e bipedal robot ankle impedance model’s schematic diagram. *e disturbance torque can be an estimation based on the ankle impedance model, which can be expressed as τ � Jθ