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.
How to realize the high power factor, high efficiency, miniaturization and high power density of AC-DC converter is the key problem of battery charging applications. In this paper, an isolated AC-DC converter is propo...
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ISBN:
(数字)9798331521950
ISBN:
(纸本)9798331521967
How to realize the high power factor, high efficiency, miniaturization and high power density of AC-DC converter is the key problem of battery charging applications. In this paper, an isolated AC-DC converter is proposed. The input voltage is rectified by the first stage AC-DC conversion, and the output is stabilized by the series resonant converter at the secondary stage. A sinusoidal modulation method is adopted to realize the constant current output characteristic independent of load. Then through the output current control loop and the PFC control loop, the constant current output and input high power factor are realized. The design of high switching frequency and resonant frequency provides conditions for high power density and miniaturization of converter design. Finally, the simulation of rated power of 960W was built by Matlab-simulink, which verified the rationality of the converter design.
The sccheduling for pushing plan during the coking process critically affects the efficiency and stability of production. However, the complexity with mutiple-stage during production makes it difficult to design an ef...
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The problem of generating optimal paths for curvature-constrained unmanned aerial vehicles (UAVs) performing surveillance of multiple ground targets is addressed in this paper. UAVs are modeled as Dubins vehicles so...
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The problem of generating optimal paths for curvature-constrained unmanned aerial vehicles (UAVs) performing surveillance of multiple ground targets is addressed in this paper. UAVs are modeled as Dubins vehicles so that the constraints of UAVs' minimal turning radius can be taken into account. In view of the effective surveillance range of the sensors equipped on UAVs, the problem is formulated as a Dubins traveling salesman problem with neighborhood (DTSPN). Considering its prohibitively high computational complexity, the Dubins paths in the sense of terminal heading relaxation are introduced to simplify the calculation of the Dubins distance, and a boundary-based encoding scheme is proposed to determine the visiting point of every target neighborhood. Then, an evolutionary algorithm is used to derive the optimal Dubins tour. To further enhance the quality of the solutions, a local search strategy based on approximate gradient is employed to improve the visiting points of target neighborhoods. Finally, by a minor modification to the individual encoding, the algorithm is easily extended to deal with other two more sophisticated DTSPN variants (multi-UAV scenario and multiple groups of targets scenario). The performance of the algorithm is demonstrated through comparative experiments with other two state-of-the-art DTSPN algorithms identified in literature. Numerical simulations exhibit that the algorithm proposed in this paper can find high-quality solutions to the DTSPN with lower computational cost and produce significantly improved performance over the other algorithms.
This paper is devoted to further investigating the cloud controlsystems(CCSs). The benefits and challenges of CCSs are provided. Both new research results of ours and some typical work made by other researchers are p...
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This paper is devoted to further investigating the cloud controlsystems(CCSs). The benefits and challenges of CCSs are provided. Both new research results of ours and some typical work made by other researchers are presented. It is believed that the CCSs can have huge and promising effects due to their potential advantages.
Optical topological insulators, as an emerging type of photonic material, present substantial benefits for optical communication. The advanced pattern recognition capabilities of deep learning have propelled the inver...
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A model-based offline policy iteration(PI) algorithm and a model-free online Q-learning algorithm are proposed for solving fully cooperative linear quadratic dynamic games. The PI-based adaptive Q-learning method can ...
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A model-based offline policy iteration(PI) algorithm and a model-free online Q-learning algorithm are proposed for solving fully cooperative linear quadratic dynamic games. The PI-based adaptive Q-learning method can learn the feedback Nash equilibrium online using the state samples generated by behavior policies, without sending inquiries to the system model. Unlike the existing Q-learning methods, this novel Q-learning algorithm executes both policy evaluation and policy improvement in an adaptive *** prove the convergence of the offline PI algorithm by proving its equivalence to Newton's method while solving the game algebraic Riccati equation(GARE). Furthermore, we prove that the proposed Q-learning method will converge to the Nash equilibrium under a small learning rate if the method satisfies certain persistence of excitation conditions, which can be easily met by suitable behavior policies. Our simulation results demonstrate the good performance of the proposed online adaptive Q-learning algorithm.
Due to the demand for energy efficiency in electro-hydraulic systems, the separate meter in and separate meter out(SMISMO) control system attracts vast attention. In this paper, the SMISMO control system was configure...
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Due to the demand for energy efficiency in electro-hydraulic systems, the separate meter in and separate meter out(SMISMO) control system attracts vast attention. In this paper, the SMISMO control system was configured with two servo valves to control the meter in and meter out *** designing two of the proposed indirect adaptive robust dynamic surface controllers(IARDSC)for the working-side and off-side system and setting the coupled items as estimated parameters, the SMISMO control system was decoupled into two subsystems completely. Here, indirect adaptive robust control(IARC) was employed to address the internal parameter uncertainties and external *** surface control(DSC) was utilized in the backstepping design procedure of IARC to deal with the inherent ‘explosion of terms' problem. As thus, the proposed IARDSC could simplify the design procedure, decrease the computational cost, and achieve an improved control performance in practical use. Finally, experimental results validated the effectiveness of proposed IARDSC and showed that the proposed SMISMO control system could provide a possibility to save more energy.
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