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To identify the dexterity of spacesuit gloves, they need to undergo bending tests in the development process. The ideal way is to place a humanoid robotic hand into the spacesuit glove, mimicking the motions of a human hand and measuring the bending angle/force of the spacesuit glove. However, traditional robotic hands are too large to enter the narrow inner space of the spacesuit glove and perform measurements. This paper aims to design a humanoid robot hand that can wear spacesuit gloves and perform measurements.

The proposed humanoid robotic hand is composed of five modular fingers and a parallel wrist driven by electrical linear motors. The fingers and wrist can be delivered into the spacesuit glove separately and then assembled inside. A mathematical model of the robotic hand is formulated by using the geometric constraints and principle of virtual work to analyze the kinematics and statics of the robotic hand. This model allows for estimating the bending angle and output force/torque of the robotic hand through the displacement and force of the linear motors.

A prototype of the robotic hand, as well as its testing benches, was constructed to validate the presented methods. The experimental results show that the whole robotic hand can be transported to and assembled in a spacesuit glove to measure the motion characteristics of the glove.

The proposed humanoid robotic hand provides a new method for wearing and measuring the spacesuit glove. It can also be used to other gloves for special protective suits that have highly restricted internal space.

The vehicle sideslip angle is an important state of vehicle lateral dynamics and its knowledge is crucial for the successful implementation of advanced driver-assistance systems. Measuring the vehicle sideslip angle on a production vehicle is challenging because of the exorbitant price of a physical sensor. This paper aims to present a novel framework for virtually sensing/estimating the vehicle sideslip angle. The desired level of accuracy for the estimator is to be within +/− 0.2 degree of the actual sideslip angle of the vehicle. This will make the precision of the proposed estimator at par with expensive commercially available sensors used for physically measuring the vehicle sideslip angle.

The proposed estimator uses an adaptive tire model in conjunction with a model-based observer. The performance of the estimator is evaluated through experimental tests on a rear-wheel drive vehicle.

Detailed experimental results show that the developed system can reliably estimate the vehicle sideslip angle during both steady state and transient maneuvers, within the desired accuracy levels.

This paper presents a novel framework for vehicle sideslip angle estimation. The presented framework combines an adaptive tire model, an unscented Kalman filter-based axle force observer and data from tire mounted sensors. Tire model adaptation is achieved by making extensions to the magic formula, by accounting for variations in the tire inflation pressure, load, tread-depth and temperature. Predictions with the adapted tire model were validated by running experiments on the Flat-Trac® machine. The benefits of using an adaptive tire model for sideslip angle estimation are demonstrated through experimental tests. The performance of the observer is satisfactory, in both transient and steady state maneuvers. Future work will focus on measuring tire slip angle and road friction information using tire mounted sensors and using that information to further enhance the robustness of the vehicle sideslip angle observer.

The purpose of this study is to propose a torque vectoring control system for improving the handling stability of distributed drive electric buses under complicated driving conditions. Energy crisis and environment pollution are two key pressing issues faced by mankind. Pure electric buses are recognized as the effective method to solve the problems. Distributed drive electric buses (DDEBs) as an emerging mode of pure electric buses are attracting intense research interests around the world. Compared with the central driven electric buses, DDEB is able to control the driving and braking torque of each wheel individually and accurately to significantly enhance the handling stability. Therefore, the torque vectoring control (TVC) system is proposed to allocate the driving torque among four wheels reasonably to improve the handling stability of DDEBs.

The proposed TVC system is designed based on hierarchical control. The upper layer is direct yaw moment controller based on feedforward and feedback control. The feedforward control algorithm is designed to calculate the desired steady-state yaw moment based on the steering wheel angle and the longitudinal velocity. The feedback control is anti-windup sliding mode control algorithm, which takes the errors between actual and reference yaw rate as the control variables. The lower layer is torque allocation controller, including economical torque allocation control algorithm and optimal torque allocation control algorithm.

The steady static circular test has been carried out to demonstrate the effectiveness and control effort of the proposed TVC system. Compared with the field experiment results of tested bus with TVC system and without TVC system, the slip angle of tested bus with TVC system is much less than without TVC. And the actual yaw rate of tested bus with TVC system is able to track the reference yaw rate completely. The experiment results demonstrate that the TVC system has a remarkable performance in the real practice and improve the handling stability effectively.

In view of the large load transfer, the strong coupling characteristics of tire , the suspension and the steering system during coach corning, the vehicle reference steering characteristics is defined considering vehicle nonlinear characteristics and the feedforward term of torque vectoring control at different steering angles and speeds is designed. Meanwhile, in order to improve the robustness of controller, an anti-integral saturation sliding mode variable structure control algorithm is proposed as the feedback term of torque vectoring control.

The aim of this paper is to investigate the effect of wing kinematics change on force generation produced by flapping wings.

Forces produced by flapping wings are measured using a load cell and compared for the investigation. The measured forces are validated by estimation using an unsteady blade element theory.

From the measurement and estimation, the authors found that flapping wings produced positive and negative lifts when the wings are attached with the +30° and −30°, respectively.

The authors quantified the characteristics of change in the force generation by flapping wings for three wing kinematics. The wing kinematics was modified by changing the initial wing attachment angle.

The result may be applicable to design of control mechanism for an insect‐mimicking flapping‐wing micro air vehicle, which has only wings without control surfaces at its tail.

The preliminary work may provide an insight for design strategy of flapping‐wing micro air vehicles with compact and handy configurations, because they may perform controlled flight even without control surfaces at their tails.

The work included here is the first attempt to quantify the force generation characteristics for different wing kinematics. The suggested way of wing kinematics change can provide a concept for control mechanism of a flapping‐wing micro air vehicle.

Discusses the 27 papers in ISEF 1999 Proceedings on the subject of electromagnetisms. States the groups of papers cover such subjects within the discipline as: induction machines; reluctance motors; PM motors; transformers and reactors; and special problems and applications. Debates all of these in great detail and itemizes each with greater in‐depth discussion of the various technical applications and areas. Concludes that the recommendations made should be adhered to.

The purpose of the work is to design a flapping wing that generates net positive propulsive force and vertical force over a flapping cycle operating at a given freestream velocity. In addition, an optimal wing is designed based on the comparison of the force estimated from the quasi‐steady theory, with the wind‐tunnel experiments. Based on the designed wing configuration, a flapping wing ornithopter is fabricated.

This paper presents a theoretical aerodynamic model of the design of an ornithopter with specific twist distribution that results generation of substantial net positive vertical force and thrust over a cycle at non‐zero advance ratio. The wing has a specific but different twist distribution during the downstroke and the upstroke that maintains the designed angle of attack during the strokes. The wing is divided into spanwise strips and Prandtl's lifting line theory is applied to estimate aerodynamic forces with the assumptions of quasi‐steady flow and the wings are without any dihedral or anhedral. Spanwise circulation distribution is obtained and hence lift is calculated. The lift is resolved along the freestream velocity and perpendicular to the freestream velocity to obtain vertical force and propulsive thrust force. Experiments are performed in a wind tunnel to find the forces generated in a flapping cycle which compares well with the theoretical estimation at low flying speeds.

The estimated aerodynamic force indicates whether the wing geometry and operating conditions are sufficient to carry the weight of the vehicle for a sustainable flight. The variation of the aerodynamic forces with varying flapping frequencies and freestream velocities has been illustrated and compared with experimental data that shows a reasonable match with the theoretical estimations. Based on the calculations a prototype has been fabricated and successfully flown.

The theory does not take into account the unsteady effects and estimates the aerodynamic forces at wing level condition. It doesn’t predict stall and ignores structural deformations due to aerodynamic loads. The airfoil section is only specified by the chord, zero lift angle of attack, lift slope, profile drag coefficient and angle of attack as given inputs. To fabricate a light weight wing that maintains a very accurate geometric twist and camber distribution as per the theoretical requirement is challenging.

Useful for designing ornithopter wing (preferably bigger) involving an unswept rigid spar with flapping and twisting.

The novelty of the present wing design is the appropriate spanwise geometric twisting about the leading edge spar.

In customized production such as plate workpiece grinding, because of the diversity of the workpiece shapes and the positional/orientational clamping errors, great efforts are taken to repeatedly calibrate and program the robots. To change this situation, the purpose of this study is to propose a method of robotic direct grinding for unknown workpiece contour based on adaptive constant force control and human–robot collaboration.

First, an adaptive constant force controller based on stiffness estimation is proposed, which can distinguish the contact of the human hand and the unknown workpiece contour. Second, a normal vector search algorithm is developed to calculate the normal vector of the unknown workpiece contour in real-time. Finally, the force and position are controlled in the calculated normal and tangential directions to realize the direct grinding.

The method considers the disturbance of the tangential grinding force and the friction, so the robot can track and grind the workpiece contour simultaneously. The experiments prove that the method can ensure the force error and the normal vector calculating error within 0.3 N and 4°. This human–robot collaboration pattern improves the convenience of the grinding process.

The proposed method realizes constant force grinding of unknown workpiece contour in real-time and ensures the grinding consistency. In addition, combined with human–robot collaboration, the method saves the time spent in repeated calibration and programming.

Compared with other related research, this method has better accuracy and anti-disturbance capability of force control and normal vector calculation during the actual grinding process.

This paper aims to gain the real-time terrain parameters of the battlefield for the evaluation of military vehicle trafficability. In military missions, improvements in vehicle mobility have the potential to greatly increase the military operational capacity, in which vehicle trafficability plays a significant role.

In this framework, an online terrain parameter estimation method based on the Gauss-Newton algorithm is proposed to estimate the primary terrain mechanical parameters. Good estimation results are indicated, unless the initial values involved are properly selected. Correspondingly, a method of terrain classification is then presented to contribute to the selection of the initial values. This method uses the wavelet packet transform technique for feature extraction and adopts the support vector machine algorithm for terrain classification. Once the terrain type is identified, advices can be given on the initial value selection referring to the empirical terrain parameters.

On the basis of a dynamic testing system suitable for real military vehicles, the proposed algorithms are validated. High estimation accuracy of the terrain parameters is indicated on sandy loam, and good classification performance is demonstrated on four tested terrains.

The presented algorithm outperforms the existing methods, which not only realizes the online terrain parameter estimation but also develops the estimation accuracy. Moreover, its effectiveness is confirmed by real vehicle tests in practice.

The purpose of this paper is to discuss the design and verification of a new control algorithm for the drive with permanent magnet synchronous motor (PMSM) and flexible coupling based on “Forced dynamics control”. Control laws are derived and tested for the rotor and load angle control and achieve non‐oscillatory position step response with a specified settling time.

“Forced dynamics control” is a new control technique based on feedback linearization which forces rotor or load position to follow demanded position with prescribed closed‐loop dynamics. The proposed control structure is developed in two steps: first, the feedback linearisation is applied to the rotor speed and then similar technique is used for position control loop.

The proposed controller is of the cascade structure, comprising an inner speed control loop, respecting vector control principles and outer position control loop designed to control the rotor or load angle, respectively. Estimates of load torques acting on the motor and load side as inputs of control algorithms are produced in observers and used to compensate disturbances offering a certain degree of robustness. Preliminary experiments confirm that proposed system follows the ideal closed‐loop dynamics with moderate accuracy.

The focus is on experimental verification of the position control of flexible PMSM drive with two position sensors and moderate precision, where the oscillations due to hardware setup, achieved sampling frequency and corresponding observers adjustment are limited up to 50 rad s⁻¹.

The designed control structure can substantially improve control performance of industrial plants subjects to torsion oscillations.

Experimental results of a novel control structure for the PMSM drives with torsion oscillations are sufficiently promising and confirmed that the rotor and load angle responses follow the prescribed ones fairly closely.

This study aims to propose a novel method based on model learning with sparsity inducing norms for estimating dynamic gravity terms of the serial manipulators. This method is realized by operating the robot, acquiring data and filtering the features in signal acquisition to adapt to the dynamic gravity parameters.

The core principle of the method is to analyze the dictionary composition of the basis function of the model based on the dynamic equation and the Jacobian matrix of an arm. According to the structure of the basis function and the sparsity of the features, combined with joint-angle and driving-torque data acquisition, the effective features of dynamic gravity parameters are screened out using L1-norm optimization and learning algorithms.

The theoretical analysis revealed that training data obtained based on joint angles and driving torques could rapidly update dynamic gravity parameters. The simulation experiment was carried out by using the publicly available robot model and compared with the previous disassembly method to evaluate the feasibility and performance. The real 7-degree of freedom (DOF) industrial manipulator was used to further discuss the effects of the feature selection. The results show that this estimation method can be fully operational and efficient in industrial applications.

This approach is applicable to most serial robots with multi-DOF and the dynamic gravity parameters of the robot are estimated through learning and optimization. The method does not require prior knowledge of the robot arm structure and only requires joint-angle and driving-torque data acquisition under low-speed motion. Furthermore, as it is a data-driven-based method, it can be applied to gravity parameters updating.

Different from previous general robot dynamic modelling methods, the sparsity of the analytical form of dynamic equations was exploited and model learning was formulated as a convex optimization problem to achieve effective gravity parameters screening. The novelty of this estimation approach is that the method does not only require any prior knowledge but also does not require a specifically designed trajectory. Thus, this method can avoid the laborious work of parameter calibration and the induced modelling errors. By using a data-driven learning approach, the new parameter updating process can be completed conveniently when the robot carries additional mass or the end-effector changes for different tasks.