Virtual Model Control Research Articles

Control of trotting gait for load-carrying quadruped walking vehicle with eccentric torso

Aiming at the problems of common methods in trotting gait control of a load-carrying quadruped walking vehicle, a control method, combining virtual model and centroidal dynamics, is proposed. The control of the walking vehicle is divided into two parts, meaning the motion control of the vehicle body and the motion control of the swing leg. The virtual model control method is used to work out the accelerations of the vehicle body, while the centroidal dynamics approach is used to obtain the resultant forces acting on the vehicle. Next, quadratic programming is used to distribute the resultant forces to the foot-ends of the supporting legs. Last, combining the Jacobian matrices of supporting legs, the vehicle body’s motion control is achieved. The virtual forces, acting on the swing leg foot-end, are obtained using the virtual model control method. Combining the swing leg’s Jacobian matrix, joint torques of swing leg are worked out. Simulink and Adams are adopted to jointly simulate omnidirectional trotting of the vehicle, under the condition of fixed and shifting position of eccentric weight. The effects of the virtual model and centroidal dynamics control method are compared with that of the virtual model control method. The results show that the errors of roll angle and pitch angle are reduced by 50%, 89% and 50%, 80%, respectively, as derived by virtual model and centroidal dynamic control method, under the two conditions. The proposed control algorithm is proved effective.

Virtual Model Control for Quadruped Robots

Virtual model control is a motion control framework that uses virtual components to create virtual forces/torques, which are actually generated by joint actuators when the virtual components interact with robot systems. Firstly, this paper employs virtual model control to do a dynamic balance control of whole body of quadruped robots' trot gait in a bottom controller. In each leg, there exists a designed swing phase virtual model control and a stance phase counterparts. In the whole body, virtual model control is utilized to achieve a attitude control containing roll, pitch and yaw. In the attitude control, a forces/torques distribution method between two stance legs is pre-investigated. In a high-level implemented controller, an intuitive velocity control approach proposed by Raibert is applied for the locomotion of quadruped robots. Secondly, an anti-disturbance control, which contains compensating gravity, adjusting step length, adjusting swing trajectory, adjusting attitude, and adjusting virtual forces/torques, is investigated to improve the robustness, terrain adaptability, and dynamic balance performance of quadrupedal locomotion. Thirdly, a trajectory tracking control method based on an intuitive velocity control is addressed through considering four factors: terrain complexity index, curvature radius of given trajectory, distance to terminal, and maximum velocity of quadruped robots. Finally, simulations validate the effectiveness of proposed controllers.

A Novel Dynamic Locomotion Control Method for Quadruped Robots Running on Rough Terrains

Quadruped robots have excellent application prospects whereas the locomotion control of them on rough terrains is still a challenging problem, especially for those of large scales. The existing methods are either too complicated or lack of accuracies due to assumptions used. This paper presents a novel control algorithm for quadruped robots running on rough terrains inspired by the virtual model control and the model predictive control. State recursions are carried out based on the dynamic model of the trunk during the standing phase. The modeling of the body is implemented in the self-defined motion reference frame that avoids global state estimations and accumulative errors. The force distribution of the standing legs is realized by quadratic optimization involving state predictions. Forces of the swing legs are calculated by the virtual spring-damping model that follow the desired trajectory which is robust to external disturbances. These two sub-controllers are combined by the time-force based state machine. Simulation results show that the quadruped robot obtains the adaptability to rough terrains and robustness to lateral pushes with the proposed method.

Virtual synchronous generator model control of PV for improving transient stability and damping in a large‐scale power system

AbstractBecause of the significant changes in environmental policies and electric power deregulation in the last decade, a lot of photovoltaic generations (PV) have been and will be installed into the power system in Japan and the ratio of PVs to other synchronous generators will be increased. As a countermeasure against the decrease in the rotational inertia in the whole power system, a virtual synchronous generator (VSG) model control of the PV has so far been proposed. However, the system stabilization effect of the VSG in large‐scale power systems has been unclear. In this paper, a virtual step‐out blocking method of VSG for improving the transient stability is proposed. In addition, the necessity of governor control of VSG in a large‐scale power system is discussed. Finally, the rated kw and kwh capacities of the battery required for realizing the VSG‐model control are evaluated.

On the Implementation of Fuzzy VMC for an Under Actuated System

Most of control strategies are based on complex mathematical equations and the success of them is directly related to the precise acquisition of the mathematical model of the system. Virtual Model Control (VMC) allows the system to be mechanically controlled like a puppet with intuitive approaches instead of complex mathematical equations. In this paper, a novel implementation of fuzzy VMC on inverted pendulum, which is an under actuated mechanism, is presented. The cart of the inverted pendulum is controlled by manipulating the vertical equilibrium point of the pendulum with two cascaded VMCs. A Takagi-Sugeno fuzzy parameter tuner is designed to improve the VMC performance. An LQR controller is also designed to compare the performances of the controllers. The complete control system is implemented on FPGA based embedded platform in real time. The simulation and experimental results indicated that the proposed VMC successfully controls the inverted pendulum. In addition, the VMC with fuzzy parameter tuner has lower rise time, settling time, IAE and ITAE when compared to the LQR which is widely used controller in the literature.

Movements and Balance Control of a Wheel-Leg Robot Based on Uncertainty and Disturbance Estimation Method

In order to control the posture, balance and movements of a wheel-leg robot(WLR) precisely, some problems have to be solved. The major problems involve the strongly coupling of movement states, the composite uncertainty with modeling errors, the time-varying internal and the external disturbances. In this paper, a force controller based on the uncertainty and disturbance estimation(UDE) method is designed. The feedforward compensation based on dynamic model allows for compliant and more precise motion control. The UDE can estimate and compensate the composite uncertainty without any priori information effectively. The posture controller is designed based on the virtual model control. The whole controller which includes the posture controller and the movements balance controller is proposed and applied for WLR that built in Webots. The simulation results of trajectory control, balance control and robust test are presented to demonstrate the effectiveness of the whole controller.

Human-like hopping in machines

Template models of legged locomotion are powerful tools for gait analysis, but can also inspire robot design and control. In this paper, a spring-loaded inverted pendulum (SLIP) model is employed to control vertical hopping of a 2-segmented legged robot. Feed-forward and bio-inspired virtual model control using the SLIP model are compared. In the latter approach, the feedback control emulates a virtual spring between hip and foot. The results demonstrate similarity of human and robot hopping. Moreover, the feedback control proves to simplify and improve hopping control. It yields better perturbation recovery and locomotion adaptation and is even easier to tune. Thus, human-like hopping is achievable using a rather simple template-based controller, which ensures the required performance, robustness and versatility.

Virtual Synchronous Generator Model Control of PV for Improving Transient Stability and Damping in a Large-scale Power System

Because of the significant changes in environmental policies and electric power deregulation in the last decade, a lot of photovoltaic generations (PV) have been and will be installed into the power system in Japan and the ratio of PVs to other synchronous generators will be increased. As a countermeasure against the decrease in the rotational inertia in the whole power system, a virtual synchronous generator (VSG) model control of the PV has so far been proposed. However, the system stabilization effect of the VSG in large-scale power systems has been unclear. In this paper, a virtual step-out blocking method of VSG for improving the transient stability is proposed. In addition, the necessity of governor control of VSG in a large-scale power system is discussed. Finally, the rated kw and kwh capacities of the battery required for realizing the VSG-model control are evaluated.

A Neuro-Musculo-Skeletal Model of Human Standing Combining Muscle-Reflex Control and Virtual Model Control.

While neuro-musculo-skeletal models are a common tool in theoretical studies on human gait, they are rarely used for studying human motor control of standing balance. As a result, it is difficult to assess whether proposed control strategies of standing balance can be realized by the human neuromuscular structure. Nor is it clear how the human control of standing balance interacts with that of walking. Motivated by these two shortcomings, we here develop a neuro-musculo-skeletal model of human bipedal standing whose control combines spinal muscle reflexes suggested to be important in walking with a virtual model control mimicking the supraspinal regulation of balance. We show in computer simulations that the model can reproduce several aspects of human standing balance observed in experiments on postural sway. Although control improvements are necessary to capture more aspects, the model may serve as a starting for studying the combined control of standing and walking.

Standing Posture Control of Bipedal Robots with Adaptive Compliance Under Unknown Payload Variations and External Disturbances

When executing tasks, robots are required to demonstrate compliance to unexpected external disturbances or human–robot interactions, and return to the demanded posture when the disturbances or contacts are removed. Traditional Virtual Model Control (VMC) requires precise gravitational compensation to accurately control the posture of a robot. Hence, load variations or other uncertain unmodeled factors in the robot will result in offsets to its balance posture, which makes the robot deviate from the demanded posture when it is in a static state. To reject this offset without sacrificing the compliance of the robot, an adaptive controller is proposed in this paper to implement adaptive compliance on the robot, which makes the robot robust to the variations in gravitational loads in the double leg support phase. The adaptive controller is a combination of the VMC controller and an online gravitational loads estimator, in which the estimator is derived in the double leg support phase to estimate the values of these parameters and obtains an online updating law based on a Kalman optimal estimator. Then, a Lyapunov function is designed to modify and combine the controller and the online gravitational loads estimator. The experiments are conducted on a 4 DoF bipedal robot in the sagittal plane to validate the effectiveness of the controller and show that, by estimating the gravitational loads of the robot, the effects of load variations on balance posture are rejected without sacrificing compliance.

Active compliance control of the hydraulic actuated leg prototype

PurposeLegged robots are inevitably to interact with the environment while they are moving. This paper aims to properly handle these interactions. It works to actively control the joint torques of a hydraulic-actuated leg prototype and achieve compliant motion of the leg.Design/methodology/approachThis work focuses on the modelling and controlling of a hydraulic-actuated robot leg prototype. First, the design and kinematics of the leg prototype is introduced. Then the linearlized model for the hydraulic actuator is built, and a model-based leg joint torque controller is presented. Furthermore, the virtual model controller is implemented on the prototype leg to achieve active compliance of the leg. Effectiveness of the controllers are validated through the experiments on the physical platform as well as the results from simulations.FindingsThe hydraulic joint torque controller presented in this paper shows good torque tracking performance. And the actively compliant leg successfully emulates the performance of virtual passive components under dynamic situations.Originality/valueThe main contribution of this paper is that it proposed a model-based active compliance controller for the hydraulic-actuated robot leg. It will be helpful for those robots that aim to achieve versatile and safe motions.

A Simplified Control Method to Achieve Stable and Robust Quadrupedal Quasi-passive Walking with Compliant Legs

The principle of passive dynamic walking has drawn lots of attentions in the field of robotics for it provides a possibility to realize natural walking. However, stabilizing the quadrupedal passive walking remains challenging. In this paper, a novel control method is proposed to stabilize the quadrupedal quasi-passive walking. Inspired by biological concepts, this method treats the foreleg pair and hindleg pair as two bipedal walkers, and a virtual model controller is designed to maintain the quasi-passive walking of each bipedal walker independently. This control method was then verified by a planar quadrupedal model with compliant legs, which successfully achieved stable periodical walking gaits. It was found that although being controlled independently, the movement of fore and hind leg pairs still formed a time-invariant phase shift, showing remarkable resemblance to that of a walking horse. We further analyzed the influences of varying factors on the gait characteristics and stability. These analyses show the control method is robust since it can stabilize the gaits within a wide range of leg compliance parameters and resist considerably large disturbances. In addition, the optimal ranges of the leg compliance parameters for the largest stability margin were also found in this study.

Torso motion control and toe trajectory generation of a trotting quadruped robot based on virtual model control

This article presents an intuitive approach based on virtual model control for robust quadrupedal trotting. The controller consists of two main modules: support phase virtual model control for torso motion control and flight phase virtual model control for flight toe trajectory generation. We mapped the relationship between the joint torques of support legs and the torso forces. And virtual forces are applied to the torso to regulate the attitude, height, and velocities of the torso during support phase. To unify the control law, virtual forces are also applied to flight toes to track the planned trajectories that are designed based on lateral velocity of the torso and contact signals of the legs. Moreover, state machine, terrain estimator, and the high level controller are designed to control the robot trotting. Simulations of quadruped trotting versatilely on flat ground, trotting over stairs and slops as well as the impact recovery are reported to demonstrate the effectiveness and robustness of our controller.

A Dynamic Balancing Approach for a Quadruped Robot Supported by Diagonal Legs

For legged robots, the most important task is to keep balance. This paper proposes a new balance control approach. To simplify the control complexity, first, LQR (linear quadratic regulator) control was used to obtain stable state feedback for the model. Then, the 6-DOF model was stabilized by dividing the whole robot into three separate parts. After that, VMC (virtual model control) was used to change the configuration of the joints. The simulation results showed that the proposed method allowed the quadruped robot to walk stably, even when certain types of disturbance were exerted on the models. In the simulation model, to mimic real conditions, noise was added to the sensors; the algorithm was then verified as still suitable for the quadruped robot.

Virtual Routing Model and PI Rate Control Algorithm in High-band width Wireless LAN

Virtual Routing Model and PI Rate Control Algorithm in High-band width Wireless LAN

An intuitive approach for quadruped robot trotting based on virtual model control

This article presents an intuitive approach based on virtual model control for quadrupedal dynamic locomotion, aiming at simple and robust trotting control. The controller consists of two main modules: stance phase virtual model control for full control of the robot body and swing phase virtual model control for control of swing legs. We combine the decomposed virtual model control with Raibert’s method to intuitively regulate the height, speeds and attitude of the body during stance phase, with special attention to the rotation about the body diagonal line. To unify the control law and further simplify the controller, virtual model control is also implemented for swing legs to follow the planned swing foot trajectories that are self-adapting depending on the speeds of the robot. Simulations including forward trotting, lateral push recover, and lateral travel are presented to demonstrate the effectiveness and robustness of our controller.

Virtual model control of lower extremity exoskeleton for load carriage inspired by human behavior

The most significant feature of the exoskeleton system, which distinguishes it from other robotic systems, is the symbiotic relationship between the exoskeleton and the wearer. For perfect symbiotic relationship, the exoskeleton should be able to exactly detect the wearer's intention to move. Existing methods by which lower extremity exoskeletons can detect human intentions are highly dependent on additional sensor systems or accurate dynamic models. In this paper, we propose a novel method for detecting human intention inspired by human behavior, and a control method that utilizes it. We define human intention as the tendency of humans to maintain a statically stable posture and minimize joint torques when supporting payloads. The control method reduces the computational requirements and simplifies the exoskeleton sensor system compared to existing methods. The experimentally measured ground reaction force was used to indirectly estimate the effects of our method on the wearer. The results suggest that the proposed method reduces the load acting on the wearer during locomotion under loaded conditions, and results in a portion of his body weight being supported by the exoskeleton when he is in an uncomfortable position.

A novel locomotion synthesis and optimisation framework for insects

The motion modelling of insects is challenging because of their small size, high frequency movements and delicate dynamics model. This paper presents a novel framework which is specially tailored to synthesise this particular type of locomotion, inspired by the biological observation of the existence of Central Pattern Generator (CPG) which regulates the cyclic motion of creatures. In our method, the CPG is organically integrated with the modelling of dynamics with assistance of the abstract actuation mechanism, Virtual Model Control, to provide physically plausible results. To achieve realistic and natural motion, it is often not practical to manually set up the control parameters and we develop an automatic strategy to optimise such non-linear non-convex problem with the Covariance Matrix Adaptation which selects suitable candidates through an evolutionary process. This framework offers high level of control of characters' motion states, speed and directions, and is flexible to adapt characters' motion to perturbations and complex environments.

Selective control of gait subtasks in robotic gait training: foot clearance support in stroke survivors with a powered exoskeleton

BackgroundRobot-aided gait training is an emerging clinical tool for gait rehabilitation of neurological patients. This paper deals with a novel method of offering gait assistance, using an impedance controlled exoskeleton (LOPES). The provided assistance is based on a recent finding that, in the control of walking, different modules can be discerned that are associated with different subtasks. In this study, a Virtual Model Controller (VMC) for supporting one of these subtasks, namely the foot clearance, is presented and evaluated.MethodsThe developed VMC provides virtual support at the ankle, to increase foot clearance. Therefore, we first developed a new method to derive reference trajectories of the ankle position. These trajectories consist of splines between key events, which are dependent on walking speed and body height. Subsequently, the VMC was evaluated in twelve healthy subjects and six chronic stroke survivors. The impedance levels, of the support, were altered between trials to investigate whether the controller allowed gradual and selective support. Additionally, an adaptive algorithm was tested, that automatically shaped the amount of support to the subjects’ needs. Catch trials were introduced to determine whether the subjects tended to rely on the support. We also assessed the additional value of providing visual feedback.ResultsWith the VMC, the step height could be selectively and gradually influenced. The adaptive algorithm clearly shaped the support level to the specific needs of every stroke survivor. The provided support did not result in reliance on the support for both groups. All healthy subjects and most patients were able to utilize the visual feedback to increase their active participation.ConclusionThe presented approach can provide selective control on one of the essential subtasks of walking. This module is the first in a set of modules to control all subtasks. This enables the therapist to focus the support on the subtasks that are impaired, and leave the other subtasks up to the patient, encouraging him to participate more actively in the training. Additionally, the speed-dependent reference patterns provide the therapist with the tools to easily adapt the treadmill speed to the capabilities and progress of the patient.

HUMANOID FALL AVOIDANCE USING A MIXTURE OF STRATEGIES

If we are to one day rely on robots as assistive devices they should be capable of mitigating the impact of random disturbances and avoid falling. Humans are surprisingly apt at remaining on their feet when pushed; they rely on reflexes such as bending the ankles and/or the hips, or by taking a step if the magnitude of the disturbance is relatively large. This paper presents a fall avoidance scheme that is capable of applying both ankle and hip strategies on a humanoid robot. While both strategies serve the same purpose, the hip strategy can absorb larger disturbances but has a higher energy overhead and should be avoided when it is not necessary. Our system is capable of detecting at the onset of a disturbance if an ankle or hip strategy is more appropriate. The decision is taken based on a 'decision surface' that is delimited by threshold values of the robot's state variables. The control is based on the Virtual Model Control (VMC) approach. The system is tested on a simulated robot developed under Gazebo as well as on a real small-scale humanoid robot. Results show successful fall avoidance with an ability to choose the optimum fall avoidance strategy.