Distributed Dynamic Load in Structural Dynamics by the Impulse-Based Force Estimation Algorithm

This paper proposes a novel approach for identifying distributed dynamic loads in the time domain.Using polynomial andmodal analysis,the load is transformed intomodal space for coefficient identification.This allows the distributed dynamic load with a two-dimensional form in terms of time and space to be simultaneously identified in the form of modal force,thereby achieving dimensionality reduction.The Impulse-based Force Estimation Algorithm is proposed to identify dynamic loads in the time domain.Firstly,the algorithm establishes a recursion scheme based on convolution integral,enabling it to identify loads with a long history and rapidly changing forms over time.Secondly,the algorithm introduces moving mean and polynomial fitting to detrend,enhancing its applicability in load estimation.The aforementioned methodology successfully accomplishes the reconstruction of distributed,instead of centralized,dynamic loads on the continuum in the time domain by utilizing acceleration response.To validate the effectiveness of the method,computational and experimental verification were conducted.

Method for Six-Legged Robot Stepping on Obstacles by Indirect Force Estimation

Adaptive gaits for legged robots often requires force sensors installed on foot-tips,however impact,temperature or humidity can affect or even damage those sensors.Efforts have been made to realize indirect force estimation on the legged robots using leg structures based on planar mechanisms.Robot Octopus III is a six-legged robot using spatial parallel mechanism（UP-2UPS） legs.This paper proposed a novel method to realize indirect force estimation on walking robot based on a spatial parallel mechanism.The direct kinematics model and the inverse kinematics model are established.The force Jacobian matrix is derived based on the kinematics model.Thus,the indirect force estimation model is established.Then,the relation between the output torques of the three motors installed on one leg to the external force exerted on the foot tip is described.Furthermore,an adaptive tripod static gait is designed.The robot alters its leg trajectory to step on obstacles by using the proposed adaptive gait.Both the indirect force estimation model and the adaptive gait are implemented and optimized in a real time control system.An experiment is carried out to validate the indirect force estimation model.The adaptive gait is tested in another experiment.Experiment results show that the robot can successfully step on a 0.2 m-high obstacle.This paper proposes a novel method to overcome obstacles for the six-legged robot using spatial parallel mechanism legs and to avoid installing the electric force sensors in harsh environment of the robot＇s foot tips.

Fuzzy Sliding Mode Control Based on Longitudinal Force Estimation for Electro-mechanical Braking Systems using BLDC Motor

This paper focuses on the controller design using fuzzy sliding mode control(FSMC)with application to electro-mechanical brake(EMB)systems using BLDC Motor.The EMB controller transmits the control signal to the motor driver to rotate the motor.The torque distribution of motors is studied in this paper actually.Firstly,the model of the EMB system is established.Then the state observer is developed to estimate the vehicle states including the vehicle velocity and longitudinal force.Due to the fact that the EMB system is nonlinear and uncertain,a FSMC strategy based on wheel slip ratio is proposed,where both the normal and emergency braking conditions are taken into account.The equivalent control law of sliding mode controller is designed on the basis of the variation of the front axle and rear axle load during the brake process,while the switching control law is adjusted by the fuzzy corrector.The simulation results illustrate that the FSMC strategy has the superior performance,better adaptability to various types of roads,and shorter braking distance,as compared to PID control and traditional sliding mode control technologies.Finally,the hardware-in-loop(HIL)experimental results have exemplified the validation of the developed methodology.

NP-MBO:A newton predictor-based momentum observer for interaction force estimation of legged robots

Swift perception of interaction forces is a crucial skill required for legged robots to ensure safe human-robot interaction and dynamic contact management.Proprioceptive-based interactive force is widely applied due to its outstanding cross-platform versatility.In this paper,we present a novel interactive force observer,which possesses superior dynamic tracking performance.We propose a dynamic cutoff frequency configuration method to replace the conventional fixed cutoff frequency setting in the traditional momentum-based observer(MBO).This method achieves a balance between rapid tracking and noise suppression.Moreover,to mitigate the phase lag introduced by the low-pass filtering,we cascaded a Newton Predictor(NP)after MBO,which features simple computation and adaptability.The precision analysis of this method has been presented.We conducted extensive experiments on the point-foot biped robot BRAVER to validate the performance of the proposed algorithm in both simulation and physical prototype.

Active compliance and force estimation of a continuum surgical manipulator based on the tip-pose feedback

Continuum manipulators have been applied in different surgical scenarios due to their dexterity and multi-DoF(degree of freedom)design compactness.To improve surgery safety,it is preferable to enable active compliance and force sensing abilities for a continuum manipulator.Existing works on active compliance and force sensing often rely on force sensors at the proximal or the distal ends,which inevitably increases the system complexity.In this paper,a shape reconstruction algorithm,a compliant motion controller,and a force estimation method are proposed successively based on the manipulator's tip pose via visual feedback.Four support vector regression(SVR)trainers are constructed and trained to compensate for the actuation residues,which are the differences between the actual actuation lengths outputs at the actuators and the ideal actuation lengths calculated from the estimated shape using the kinematics model,under no-load condition.Then,a compliant motion controller and a force estimation method are realized based on the current actuation residues,compared with the actuation residues under the no-load condition.In this way,no additional sensors are needed as an endoscopic camera is often available in a laparoscopic or endoscopic surgical system.The experiments were conducted on aφ3 mm-continuum manipulator to demonstrate the effectiveness of the proposed algorithms.

State Estimation of Drive-by-Wire Chassis Vehicle Based on Dual Unscented Particle Filter Algorithm

Accurate vehicle dynamic information plays an important role in vehicle driving safety.However,due to the characteristics of high mobility and multiple controllable degrees of freedom of drive-by-wire chassis vehicles,the current mature application of traditional vehicle state estimation algorithms can not meet the requirements of drive-by-wire chassis vehicle state estimation.This paper proposes a state estimation method for drive-by-wire chassis vehicle based on the dual unscented particle filter algorithm,which make full use of the known advantages of the four-wheel drive torque and steer angle parameters of the drive-by-wire chassis vehicle.In the dual unscented particle filter algorithm,two unscented particle filter transfer information to each other,observe the vehicle state information and the tire force parameter information of the four wheels respectively,which reduce the influence of parameter uncertainty and model parameter changes on the estimation accuracy during driving.The performance with the dual unscented particle filter algorithm,which is analyzed in terms of the time-average square error,is superior of the unscented Kalman filter algorithm.The effectiveness of the algorithm is further verified by driving simulator test.In this paper,a vehicle state estimator based on dual unscented particle filter algorithm was proposed for the first time to improve the estimation accuracy of vehicle parameters and states.

Vertical Tire Forces Estimation of Multi-Axle Trucks Based on an Adaptive Treble Extend Kalman Filter

Vertical tire forces are essential for vehicle modelling and dynamic control.However,an evaluation of the vertical tire forces on a multi-axle truck is difficult to accomplish.The current methods require a large amount of experimental data and many sensors owing to the wide variation of the parameters and the over-constraint.To simplify the design process and reduce the demand of the sensors,this paper presents a practical approach to estimating the vertical tire forces of a multi-axle truck for dynamic control.The estimation system is based on a novel vertical force model and a proposed adaptive treble extend Kalman filter(ATEKF).To adapt to the widely varying parameters,a sliding mode update is designed to make the ATEKF adaptive,and together with the use of an initial setting update and a vertical tire force adjustment,the overall system becomes more robust.In particular,the model aims to eliminate the effects of the over-constraint and the uneven weight distribution.The results show that the ATEKF method achieves an excellent performance in a vertical force evaluation,and its performance is better than that of the treble extend Kalman filter.

A Simplified Model, Dynamic Analysis and Force Estimation for a Large-scale Orinthopter in Forward Flight Based on Flight Data

Similarities and differences of a large-scale flapping-wing robot with fixed-wing UAVs in equations of motion,trim curves,and aerodynamic forces in forward flight are discussed in this paper and a simplified model for flapping flight is presented.Due to the high Wing to Total Weight(WTW)ratio of large-scale omithopters,simple rigid body dynamics is not accurate enough for flight dynamics modeling.On the other hand,the multi-body dynamics associated with flapping gives little insight into the behavior of the resulting model due to complexity of equations.It is also difficult to design proper controllers for such complicated models.In this paper,the effects of different terms of multi-body equations of ornithopter on the estimated aerodynamic forces are studied via experimental flight data.A simpler but yet accurate set of equations is obtained by removing less effective terms from original relations.The presented model is in the form of normal aircraft equations plus some additional terms which can be used in different control and estimation processes.In addition,trim conditions of forward flight are extracted using several flight tests,and corresponding periodic behavior of states and forces are studied.These studies are applicable for identifying time-periodic models.

WAVE CURRENT FORCE COEFFICIENTS ON INCLINED CYLINDER AND A NEW ESTIMATION METHOD

Based on the review of present force coefficients estimation methods, a new method in the frequency domain, revised cross-spectrum estimation method, is presented in this paper. Some experiments on the wave-current force on inclined cylinders are also described and the wave current force coefficients are estimated by the revised cross-spectrum estimation method. From the results, it is found that the wave and current directions have some regular effect on the coefficients. According to the results, some empirical formulas are obtained for converting the wave-current force coefficients on inclined cylinders into a unified coefficient. Comparisons show that the unified coefficients are in good agreement with other results.

Estimation of the interaction force between human and passive lower limb exoskeleton device during level ground walking

To develop sophisticated and efficient control strategies for exoskeleton devices,acquiring the information of interaction forces between the wearer and the wearable device is essential.However,obtaining the interaction force via conventional methods,such as direct measurement using force sensors,is problematic.This paper proposes a kinematic data-based estimation method to evaluate the interaction force between human lower limbs and passive exoskeleton links during level ground walking.Unlike conventional methods,the proposed method requires no force sensors and is computationally cheaper to obtain the calculation results.To obtain more accurate kinematic data,a marker refinement algorithm based on bilevel optimization framework is adopted.The interaction force is evaluated by a spring model,which is used to imitate the binding behavior between human limbs and the exoskeleton links.The deflection of the spring model is calculated based on the assumption that the phase delay between human limb and exoskeleton link can be presented by the sequence of frames of kinematic data.Experimental results of six subjects indicate that our proposed method can estimate the interaction forces during level ground walking.Moreover,a case study of bandage location optimization is conducted to demonstrate the usefulness of obtaining the interaction information.

Numerical estimation of bank-propeller-hull interaction effect on ship manoeu-vring using CFD method

This paper presents a numerical investigation of ship manoeuvring under the combined effect of bank and propeller. The incompressible turbulent flow with free surface around the self-propelled hull form is simulated using a commercial CFD software （ANSYS-FLUENT）. In order to estimate the influence of the bank-propeller effect on the hydrodynamic forces acting on the ship, volume forces representing the propeller are added to Navier-Stokes equations. The numerical simulations are carried out using the equivalent of experiment conditions. The validation of the CFD model is performed by comparing the numerical results to the availa- ble experimental data. For this investigation, the impact of Ship-Bank distance and ship speed on the bank effect are tested with and without propeller. An additional parameter concerning the advance ratio of the propeller is also tested.

An innovative inertial parameters identification method for non-cooperative space targets based on electrostatic interaction

Inertial characteristics of non-cooperative targets are crucial for space capture and sub-sequent on-orbit servicing.Previous methods for identifying inertial parameters involve proximity operations,which are associated with the risk of collision with non-cooperative targets.This paper introduces a long-range,contactless method for identifying the inertial parameters of a non-cooperative target during the pre-capture phase.Specifically,electrostatic interaction is used as an external excitation to alter the target's motion.A force estimation algorithm that uses measure-ments from visual and potential sensors is proposed to estimate the electrostatic interaction and eliminate the need for force sensors.Furthermore,a recursive estimation-identification framework is presented to concurrently estimate the coupled motion state,weak electrostatic interaction,and inertial parameters of the target.The simulation results show that the proposed method extends the identification distance to 170 times that of the previous method while maintaining high identifica-tion precision forall parameters.