Papers by Keyword: Variable Structure

Abstract: A sliding-mode attenuating variable-rate reaching control strategy for three-phase current source inverter is presented. The proposed control strategy significantly improves solve the exist issues that the slow dynamic characteristic and the output waveform distortion using linear control technology in three-phase current source inverter. In order to facilitate the analysis and design of sliding mode controller, a new mathematical model of three-phase current source inverter is built, and it is further simplified through the spatial coordinate transformation. The switching surfaces and the attenuating variable-rate reaching control law are deduced. Finally, the simulation results verify the effectiveness and feasibility of the control strategy for three-phase current source inverter.

Abstract: Due to the parametric and structural uncertainty of the DC drive system, an adaptive control method is necessary. Therefore, an original model reference adaptive control (MRAC) for DC drives is proposed in this paper. MRAC ensures on-line adjustment of the control parameters with DC machine parameter variation. The proposed adaptive control structure provides regulating advantages: asymptotic cancellation of the tracking error, fast and smooth evolution towards the origin of the phase plan due to a sliding mode switching k-sigmoid function. The reference model can be a real strictly positive function (the tracking error is also the identification error) as its order is relatively higher than one degree. For this reason, the synthesis of the adaptive control will use a different type of error called augmented or enhanced error. The DC machine with separate excitation is fed at a constant flux. This adaptive control law assures robustness to external perturbations and to unmodelled dynamics.

Abstract: For high-power current source inverter work object is a nonlinear time-varying systems, which could easily lead to the inverter voltage and current output waveform distortion, this paper firstly proposes a new variable-rate reaching sliding mode control scheme to solve the above problems existing in current source inverter system. In this scheme, we construct the variable structure model of the system, determine the sliding surface, give the variable-rate reaching control law and deduce the sliding domain. At last, the simulation result proves the validity and superiority of the scheme.

Abstract: Combined with the advantages of good protection of global robot, self-equilibrium, easy control of wheeled robot and strong obstacle surmounting ability of turbofan robot, a variable structure mobile robot which has three kinds of basic modalities of global, turbofan and three-wheel is designed. The balancing leg is retracted and the two polymorphic wheels of the robot are closed into a sphere while in the global state, and it could be conveniently threw, carried and make all directional movements on the flat grounds. When confronted with the complicated terrain environments of sand, slopes etc., the two polymorphic wheels will be outspread to the turbofan state, and the balancing leg will be opened out as a third supporting wheel so as to strengthen the ability to adapt to the environment. When the two polymorphic wheels are expanded into two wheels, the robot motions are more smoothly and easily to be controlled. A virtual prototype of the robot is designed by three-dimensional technology, as well as the motion simulation. Rationality of the mechanism design scheme of the variable structure mobile robot is verified.

Abstract: In this article, a new approach to design discrete-time sliding-mode guidance laws is presented based on the target-missile relative motion equation in three-dimensional space. This method significantly reduced system chattering and could be easily achieved on engineering. Furthermore, effectiveness of the proposed guidance laws is demonstrated through simulation by comparing with the traditional proportional guidance laws.

Abstract: In order to meet the requirements of real-time and embedded of industrial field, a reconfigurable Back-Propagation neural network based on FPGA has been implemented on Xilinx's Spartan-3E (XC3S250E) chip which has 250000 gate. First the optimal network structure and weights were gotten by a variable structure of BP neural network algorithm. Then an improved hardware approaching method of excitation function was put forward, and the maximum error was 1.58% by simulation and comparative analysis on the error. Finally hardware co-imitation and timing simulation was token based on a reasonable choice of data accuracy, and then the hardware BP neural network algorithm was been downloaded and implemented on FPGA. This method has better accuracy and speed, it is an effective method of BP neural network modeling based on hardware, and lays the foundation for the hardware realization of other neural network and embedded image processing.

Abstract: Two typical methods for model reference adaptive control are introduced. By integrating the Narendra adaptive control method and the variable structure model reference adaptive control method, a new variable model reference adaptive recursive control method is presented. The results of simulation computations show that the new method has the merits of the above two methods and is efficient and effective.

Abstract: In order to obtain an appropriate control for the electrical drive systems the real parameters values must be known accurately. Moreover, due to the parametric and structural uncertainty of the DC drive system, an adaptive control method is necessary. Therefore, a new model reference adaptive control (MRAC) for DC drives is proposed in this paper. MRAC ensures on-line adjustment of the control parameters with DC machine parameter variation. The adaptive control developed in this paper assures the asymptotic cancellation of the tracking error, fast and smooth responses of the DC drive without knowing a priory any information about the DC drive parameters. The simulation results show the validity of the proposed solution.

Abstract: A mathematic model, focusing on the control of tail plane actuator servo system, is established based on control theories. Considering its nonlinearity and intermittence, a fuzzy-PID control method is brought forward based on fuzzy theory. The design of a fuzzy-PID controller has been accomplished. and its comparision with conventional PID control and P control has been made. The final system simulation is conducted with Simulink under the effect of unit step signal.The result shows that the fuzzy-PID control has a better performance in speed, response and anti-jamming. It has a satisfactory dynamic characteristic while not losing the advantages of the fuzzy control and the PID control. Therefore, it enhances the integral property of the tail plane actuator servo system and obtains a good control effect. In a word, the new system can meet the requirement of the system better.

Abstract: Neural network models have widely been applied in assessment and perdition of economic and social fields, including risk assessment. Thus, it becomes a subject for the theory of neural network to study how to improve accuracy in the premise of ensuring convergence rate of BP (Back Propagation) neural network. On the basis of recent studies and disadvantages of traditional BP neural network, in terms of structural optimization to improve accuracy, the paper presents a variable-structure neural network where it is re-linking randomly process from neurons of input layer to neurons of output layer and from neurons of hidden layer to neurons of output layer. Secondly, the variable structure neural network of re-linking random process is applied in freeway investment risk assessment. Results of a cast indicate that the proposed model is sufficiently reasonably.