In this paper, a semi-physical simulation platform of robot teleoperation system is designed, and a combined control approach using Jacobian matrix and Proportional-Derivative(PD) algorithm is proposed. A digital low-...
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In this paper, a semi-physical simulation platform of robot teleoperation system is designed, and a combined control approach using Jacobian matrix and Proportional-Derivative(PD) algorithm is proposed. A digital low-pass filter is designed to eliminate noise signal caused by hand-vibration of surgeons. The advantages of the proposed approach include easy implementation, real-time response and accurate master-slave tracking. The results of semi-physical simulation validated that the proposed approach realized accurate master-slave tracking for puncture surgery and the noise caused by hand-vibration was eliminated effectively.
Tele-operation is a merging point of modern developments in robotics and communications technologies. Both traditional applications (e.g., mining) and emerging domains (e.g., microsurgery) benefit from the advancement...
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ISBN:
(纸本)9781479916191
Tele-operation is a merging point of modern developments in robotics and communications technologies. Both traditional applications (e.g., mining) and emerging domains (e.g., microsurgery) benefit from the advancement of tele-robotic systems. Combining a local human operator and a remote autonomous robot, the tele-robotics systems could optimally exploit both the intelligence of human operator and the automation of robot. In a tele-operation scenario, the exchange of force and position signals, i.e., haptic feedback, can greatly extend human operator's capability of conducting complicated work through the robot in a remote environment. However, long-range communications usually suffer from the time delay problem caused by the inherent characteristics of communication channels. Delayed transmission of haptic signals may lead to instability in the closed-loop telerobot controlsystem. Although much effort has been made in the control community to overcome this difficulty, and many approaches such as wave scattering, passivity, and small gain theorem have been employed as possible solutions, stability in haptic telerobot control remains a challenge. It has been noted that the neural path of human being is also subject to transmission delay as well. We know that in the presence of time delay in sensory feedback pathways, human neural control can easily maintain stability and even to show superior manipulation skills in unstable interaction scenarios. It has been discovered and reported that the operation stability of human beings could be achieved by well adjusting the mechanical impedance, i.e., the resistance to imposed motion, which is largely contributed by the spring-like property of muscles. Being investigated in robotics community for decades, impedance control has shown great advantage in terms of safety and flexibility over conventional position or force control. However, only until very recently our attention has been attracted to transferring a human operator
Early detection of rotating stall and surge in axial flow compressors is of great importance for improving the working efficiency and stability of the compressor. Based on deterministic learning (DL) theory and dynami...
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This paper considers reset controlsystems with output *** present sufficient conditions for the quadratic stability and finite L2 gain ***,the results are extended to piecewise quadratic stability which is much less ...
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ISBN:
(纸本)9781479947249
This paper considers reset controlsystems with output *** present sufficient conditions for the quadratic stability and finite L2 gain ***,the results are extended to piecewise quadratic stability which is much less ***,an iterative algorithm is proposed to design the reset *** the obtained results are given as linear matrix inequalities(LMIs) that can be solved *** examples are given to illustrate the results.
In this paper, we consider the control of large-scale processes with both input and state couplings. A distributed model predictive control(MPC) strategy for tracking based on the reference trajectories is presented. ...
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ISBN:
(纸本)9781479947249
In this paper, we consider the control of large-scale processes with both input and state couplings. A distributed model predictive control(MPC) strategy for tracking based on the reference trajectories is presented. The proposed distributed MPC strategy requires decomposing a large-scale system into several smaller ones and solving convex optimization problems independently. Distributed MPC tracking strategies for unconstrained and constrained processes are presented, respectively. An iterative algorithm is presented to coordinate the distributed MPC controllers. The proposed algorithm is applied to a four-tank process to demonstrate the effectiveness.
A novel fault integration method is proposed in this paper for manufacturing system models given in the form of timed colored Petri nets. The faults are assumed to have a stochastic nature and are represented in the f...
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ISBN:
(纸本)9789077381861
A novel fault integration method is proposed in this paper for manufacturing system models given in the form of timed colored Petri nets. The faults are assumed to have a stochastic nature and are represented in the form of transitions firing in stochastic way with known fault probabilities in the system model. A novel fault effect propagation method was also developed, that can be used to compute the probabilities of the possible faulty and non-faulty intermediate and final states of the system using the probabilities of faults and the occurrence graph. The faultless and fault containing models were implemented in CPNTools both for non-timed and timed cases. A software module was also developed for the proposed probabilistic fault propagation analysis. The proposed methods and tools were demonstrated using a simple case study.
A novel on-line diagnosis method is proposed in this paper that uses a qualitative dynamic model of the system and its colored Petri nets model. The model contains both the normal and the possible faulty operational m...
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ISBN:
(纸本)9789077381861
A novel on-line diagnosis method is proposed in this paper that uses a qualitative dynamic model of the system and its colored Petri nets model. The model contains both the normal and the possible faulty operational modes of the system. The deviation between the normal and faulty modes is characterized based on P-HAZID tables. The actual system state can be searched on the occurrence graph constructed in advance. Starting from this node the possible consequences and root causes can be determined on-line with traversing on the graph. The proposed method is illustrated on simple case studies.
As well-known, model predictive control is closely related to optimal control. This paper studies relationships between them and provides a unified framework for optimality analysis of model predictive controllers (MP...
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As well-known, model predictive control is closely related to optimal control. This paper studies relationships between them and provides a unified framework for optimality analysis of model predictive controllers (MPC). The optimality is evaluated by comparing total performance of MPC with finite and infinite horizon optimal cost. Based on relaxed value iteration method, upper and lower bounds of optimality evaluation functions are expressed explicitly in terms of optimization horizon. These results reveal detailed characteristics on performance of closed-loop MPC systems due to using “receding horizon optimization” implementation style.
This paper proposes a novel nonlinear distributed consensus protocol of the finite-time consensus problems of leader-follower multi-agent systems based on the distributed consensus error functions. It is proved that t...
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This paper proposes a novel nonlinear distributed consensus protocol of the finite-time consensus problems of leader-follower multi-agent systems based on the distributed consensus error functions. It is proved that the leader-follower multi-agent systems under this nonlinear protocol can reach the consensus in finite time in the scenarios with fixed topology and two kinds of switching topologies, respectively. The results are also extended to the case with directed communication topology. Finally, some examples and simulation results are given to illustrate the effectiveness of the proposed control protocols.
Sensor networks have been widely utilized in various applications. In large wind farms, numerous sensor nodes are deployed across the field for monitoring purpose. They are required to work in harsh environment and us...
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Sensor networks have been widely utilized in various applications. In large wind farms, numerous sensor nodes are deployed across the field for monitoring purpose. They are required to work in harsh environment and usually undergo unexpected failures. This paper introduces a new method to model nodes of sensor networks by using two-layer neural networks (NN). Each node's dynamics and interconnections with other sensor network nodes are integrated into the model, whose accuracy is guaranteed by the NN's universal approximation property. Furthermore, the model can be subsequently employed to detect any incipient failures which can be modeled as a nonlinear function of state and input variables. An additional NN along with a novel simplified updating law is utilized for self-diagnostics, whose output can declare a failure alarm if it exceeds a certain threshold. Mathematical analysis is substantiated with simulation results.
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