The position tracking control problem of an electrical cylinder in the presence of dynamic friction nonlinearities in its transmission process is addressed in this paper. First, a torque decou- piing approach is propo...
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The position tracking control problem of an electrical cylinder in the presence of dynamic friction nonlinearities in its transmission process is addressed in this paper. First, a torque decou- piing approach is proposed to formulate the dynamic model. Secondly, to compensate the friction in the case of servo motion, a modified LuGre model is designed to make a continuous transition be- tween a static model at a high speed and a LuGre model at a low speed to avoid instability due to dis- cretization with a finite sampling rate. To accelerate the speed of estimating time-varying parame- ters, a fast adaption law is proposed by designing an attraction domain around a rough value related to the load force. Finally, a discontinuous projection based adaptive robust controller is synthesized to effectively handle parametric uncertainties for ensuring a guaranteed robust performance. A Lya- punov stability analysis demonstrates that all signals including tracking errors have the guaranteed convergent and bounded performance. Extensive comparative simulations with sinusoidal and point- point tracks are obtained respectively in low and high speeds. The results show the effectiveness and the achievable control performance of the proposed control strategy.
In order to meet the application requirements of autonomous vehicles, this paper proposes a simultaneous localization and mapping (SLAM) algorithm, which uses a VoxelGrid filter to down sample the point cloud data, ...
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In order to meet the application requirements of autonomous vehicles, this paper proposes a simultaneous localization and mapping (SLAM) algorithm, which uses a VoxelGrid filter to down sample the point cloud data, with the combination of iterative closest points (ICP) algorithm and Gaussian model for particles updating, the matching between the local map and the global map to quantify particles' importance weight. The crude estimation by using ICP algorithm can find the high probability area of autonomous vehicles' poses, which would decrease particle numbers, increase algorithm speed and restrain particles' impoverishment. The calculation of particles' importance weight based on matching of attribute between grid maps is simple and practicable. Experiments carried out with the autonomous vehicle platform validate the effectiveness of our approaches.
In order to solve kinematic redundancy problems of a hydraulic quadruped walking robot,which include leg dragging,sliding,impingement against the ground,an improved gait planning algorithm for this robot is proposed i...
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In order to solve kinematic redundancy problems of a hydraulic quadruped walking robot,which include leg dragging,sliding,impingement against the ground,an improved gait planning algorithm for this robot is proposed in this ***,the foot trajectory is designated as the improved composite cycloid foot ***,the landing angle of each leg of the robot is controlled to satisfy friction cone to improve the stability performance of the *** with the controllable landing angle of quadruped robot and a geometry method,the kinematic equation is derived in this ***,agait planning method of quadruped robot is proposed,a dynamic co-simulation is done with ADAMS and MATLAB,and practical experiments are *** validity of the proposed algorithm is confirmed through the co-simulation and *** results show that the robot can avoid sliding,reduce impingement,and trot stably in trot gait.
Most existing legged robots are developed under laboratory environments and, corre- spondingly, have good performance of locomotion. The robots' ability of walking on rough terrain is of great importance but is seldo...
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Most existing legged robots are developed under laboratory environments and, corre- spondingly, have good performance of locomotion. The robots' ability of walking on rough terrain is of great importance but is seldom achieved. Being compliant to external unperceived impacts is cru- cial since it is unavoidable that the slip, modeling errors and imprecise information of terrain will make planned trajectories to be followed with errors and unpredictable contacts. The impedance control gives an inspiration to realize an active compliance which allows the legged robots to follow reference trajectories and overcome external disturbances. In this paper, a novel impedance force/ position control scheme is presented, which is based on Cartesian force measurement of leg' s end effector for our hydraulic quadruped robot The simulation verifies the efficiency of the impedance model, and the experimental results at the end demonstrate the feasibility of the proposed control scheme.
A plant-friendly proportional-integral-derivative (PID) controller optimization framework is proposed to make tradeoffs among set-point response,controller output variations and *** objective function is chosen as t...
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A plant-friendly proportional-integral-derivative (PID) controller optimization framework is proposed to make tradeoffs among set-point response,controller output variations and *** objective function is chosen as the weighted sum of the integral of squared time-weighted error and the integral of squared timeweighted derivative of the control variable with respect to set-point response,while the robustness of the system is guaranteed by constraints on gain and phase *** to the complex structure of the constraints,the problem is solved by genetic *** analysis show the proposed method could efficiently reduce the controller output variations while maintaining a short settling *** on the simulation results,iterative tuning rules for the weighting factor in the objective function are obtained,which allows efficient simple proportional-integral(PI) tuning formulae to be derived.
A backstepping method based adaptive robust dead-zone compensation controller is pro- posed for the electro-hydraulic servo systems (EHSSs) with unknown dead-zone and uncertain system parameters. Variable load is se...
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A backstepping method based adaptive robust dead-zone compensation controller is pro- posed for the electro-hydraulic servo systems (EHSSs) with unknown dead-zone and uncertain system parameters. Variable load is seen as a sum of a constant and a variable part. The constant part is regarded as a parameter of the system to be estimated real time. The variable part together with the friction are seen as disturbance so that a robust term in the controller can be adopted to reject them. Compared with the traditional dead-zone compensation method, a dead-zone compensator is incor- porated in the EH$S without constructing a dead-zone inverse. Combining backstepping method, an adaptive robust controller (ARC) with dead-zone compensation is formed. An easy-to-use ARC tuning method is also proposed after a further analysis of the ARC structure. Simulations show that the proposed method has a splendid tracking performance, all the uncertain parameters can be estimated, and the disturbance has been rejected while the dead-zone term is well estimated and compensated.
This paper is concerned with the optimal fusion of sensors with cross-correlated sensor *** taking linear transformations to the measurements and the related parameters, new measurement models are established, where t...
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This paper is concerned with the optimal fusion of sensors with cross-correlated sensor *** taking linear transformations to the measurements and the related parameters, new measurement models are established, where the sensor noises are decoupled. The centralized fusion with raw data, the centralized fusion with transformed data, and a distributed fusion estimation algorithm are introduced, which are shown to be equivalent to each other in estimation precision, and therefore are globally optimal in the sense of linear minimum mean square error(LMMSE). It is shown that the centralized fusion with transformed data needs lower communication requirements compared to the centralized fusion using raw data directly, and the distributed fusion algorithm has the best flexibility and robustness and proper communication requirements and computation complexity among the three algorithms(less communication and computation complexity compared to the existed distributed Kalman filtering fusion algorithms). An example is shown to illustrate the effectiveness of the proposed algorithms.
An adaptive unscented Kalman filter (AUKF) and an augmented state method are employed to estimate the timevarying parameters and states of a kind of nonlinear high-speed objects. A strong tracking filter is employed...
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An adaptive unscented Kalman filter (AUKF) and an augmented state method are employed to estimate the timevarying parameters and states of a kind of nonlinear high-speed objects. A strong tracking filter is employed to improve the tracking ability and robustness of unscented Kalman filter (UKF) when the process noise is inaccuracy, and wavelet transform is used to improve the estimate accuracy by the variance of measurement noise. An augmented square-root framework is utilized to improve the numerical stability and accuracy of UKF. Monte Carlo simulations and applications in the rapid trajectory estimation of hypersonic artillery shells confirm the effectiveness of the proposed method.
Although different multipath error models of Delay lock loop(DLL) used in GPS receiver are established, they have never been put together for comparison. Furthermore, no universal simulation method is developed to get...
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Although different multipath error models of Delay lock loop(DLL) used in GPS receiver are established, they have never been put together for comparison. Furthermore, no universal simulation method is developed to get a fair comparison among these models. A new model with implicate expression is hence proposed for the coherent DLL and the noncoherent Dot-product(DOT) power mode DLL. Meanwhile, a new simulation method based on the anonymous function in Matlab, which is especially suitable for models with implicit expression,is also proposed to compare the new model with the existing ones. The theoretical analysis and simulation results show that the existing models are the special case of the proposed one. The new simulation method can be used for the comparison of different multipath error models and the multipath error analysis of other DLLs for which only the implicit model is available.
Industrial Internet of Things(IoT)connecting society and industrial systems represents a tremendous and promising paradigm *** IoT,multimodal and heterogeneous data from industrial devices can be easily collected,and ...
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Industrial Internet of Things(IoT)connecting society and industrial systems represents a tremendous and promising paradigm *** IoT,multimodal and heterogeneous data from industrial devices can be easily collected,and further analyzed to discover device maintenance and health related potential knowledge *** data-based fault diagnosis for industrial devices is very helpful to the sustainability and applicability of an IoT *** how to efficiently use and fuse this multimodal heterogeneous data to realize intelligent fault diagnosis is still a *** this paper,a novel Deep Multimodal Learning and Fusion(DMLF)based fault diagnosis method is proposed for addressing heterogeneous data from IoT environments where industrial devices ***,a DMLF model is designed by combining a Convolution Neural Network(CNN)and Stacked Denoising Autoencoder(SDAE)together to capture more comprehensive fault knowledge and extract features from different modal ***,these multimodal features are seamlessly integrated at a fusion layer and the resulting fused features are further used to train a classifier for recognizing potential ***,a two-stage training algorithm is proposed by combining supervised pre-training and fine-tuning to simplify the training process for deep structure models.A series of experiments are conducted over multimodal heterogeneous data from a gear device to verify our proposed fault diagnosis *** experimental results show that our method outperforms the benchmarking ones in fault diagnosis accuracy.
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