Collision avoidance is always difficult in the planning path for a mobile robot. In this paper, the virtual force field between a mobile robot and an obstacle is formed and regulated to maintain a desired distance by ...
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Collision avoidance is always difficult in the planning path for a mobile robot. In this paper, the virtual force field between a mobile robot and an obstacle is formed and regulated to maintain a desired distance by hybrid force control algorithm. Since uncertainties from robot dynamics and obstacle degrade the performance of a collision avoidance task, intelligent control is used to compensate for the uncertainties. A radial basis function （RBF） neural network is used to regulate the force field of an accurate distance between a robot and an obstacle in this paper and then simulation studies are conducted to confirm that the proposed algorithm is effective.
In order to solve the problem of trajectory tracking for a class of novel serial-parallel hybrid humanoid arm（HHA）, which has parameters uncertainty, frictions, disturbance, abrasion and pulse forces derived from mo...
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In order to solve the problem of trajectory tracking for a class of novel serial-parallel hybrid humanoid arm（HHA）, which has parameters uncertainty, frictions, disturbance, abrasion and pulse forces derived from motors, a multistep dynamics modeling strategy is proposed and a robust controller based on neural network（NN）-adaptive algorithm is designed. At the first step of dynamics modeling, the dynamics model of the reduced HHA is established by Lagrange method. At the second step of dynamics modeling, the parameter uncertain part resulting mainly from the idealization of the HHA is learned by adaptive algorithm. In the trajectory tracking controller, the radial basis function（RBF） NN, whose optimal weights are learned online by adaptive algorithm, is used to learn the upper limit function of the total uncertainties including frictions, disturbances, abrasion and pulse forces. To a great extent, the conservatism of this robust trajectory tracking controller is reduced, and by this controller the HHA can impersonate mostly human actions. The proof and simulation results testify the validity of the adaptive strategy for parameter learning and the neural network-adaptive strategy for the trajectory tracking control.
Based on the design concept of virtual instrument and the design method of function modulation, using PC machine and data acquisition card as hardware system, proposed a design of sewage multi-parameter online monitor...
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n order to meet the needs of construction of high-speed railway passenger dedicated line, 900t rubber-tyred girder hoister is researched and manufactured. Steering system of the hoister is controlled by electro-hydrau...
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This paper proposes a novel variable step size LMS algorithm based on the number of computing mechanisms by analyzing the basic principles of the variable step LMS adaptive filtering algorithms. The algorithm establis...
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This paper proposes a novel variable step size LMS algorithm based on the number of computing mechanisms by analyzing the basic principles of the variable step LMS adaptive filtering algorithms. The algorithm establishes a different nonlinear relation-ship between step factor and error signal based on the different sampling time, which not only can control step size by using sampling time indirectly, but also change the parameters to meet the requirement of fast convergence. Compared with the other variable step algorithms, this algorithm is proved to have faster convergence speed and higher stability.
A novel control strategy based on passivity theory was proposed with special attention to trajectory tracking and robust control of rigid robot. In this paper, robot model was divided into nominal model and uncertaint...
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A novel control strategy based on passivity theory was proposed with special attention to trajectory tracking and robust control of rigid robot. In this paper, robot model was divided into nominal model and uncertainty part. Based on the backstepping approach, feedback passivity was used to design controller for the nominal model. A variable structure concentrated compensation controller was adopted to the uncertainty part. Using fuzzy rules, a fuzzy system based on nominal model controller and sliding mode variable structure controller was built to eliminate chattering effectively. Simulation results show that the scheme can achieve tracking effect with high speed, as well as enhance the robustness of the system under the condition of existing model error and external disturbance, and the global stability can be also guaranteed.
Active stabilization of stall instabilities in axial flow compressors is pursued using a combination of bifurcation analysis and nonlinear control. A low-order discretization model of a PDE compressor model is found t...
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Active stabilization of stall instabilities in axial flow compressors is pursued using a combination of bifurcation analysis and nonlinear control. A low-order discretization model of a PDE compressor model is found to exhibit a stationary (pitchfork) bifurcation at the onset of stall. Using throttle opening as a control, analysis of the linearized system at stall shows that the critical mode (zero eigenvalue) is unaffected by linear feedback. Hence, nonlinear stabilization techniques are necessary. A quadratic feedback control law is proposed based on the lower-order model and is found to adequately serve the control purposes for both the lower order and higher order discretizations.
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