This paper proposes a novel model-free super-twisting nonlinear sliding mode control (MFSTNLSMC) strategy with an improved smoothing extended state observer (SESO) for permanent magnet synchronous motor (PMSM) drives. First of all, the improved SESO is introduced to estimate the unknown term of the PMSM ultra-local model. Secondly, a novel nonlinear sliding mode surface (NLSMS) is designed, which can effectively overcome the disadvantages of simple and rough signal processing of the conventional linear sliding mode surface. At the same time, a super-twisting (ST) structure is chosen to suppress the chattering phenomenon and improve system robustness. Then, the Lyapunov stability theorem is used to prove the stability of the proposed control algorithm. Finally, both comparative simulations and experimental demonstrations verify the excellent speed tracking performance and robustness of the proposed control strategy.
In this research, based on the ultra-local model, a novel compound model-free control strategy with an intelligent Proportional-Integral and super-twisting Sliding Mode Control (MFiPISTSMC) strategy for permanent magnet synchronous motor (PMSM) drives is proposed. Firstly, an intelligent Proportional-Integral (iPI) control strategy is designed for motor speed regulation. Secondly, a super-twisting Sliding Mode Control (STSMC) strategy is constructed based on the ultra-local model of PMSM. At the same time, the unknown term of the ultra-local model of PMSM is estimated by a Linear Extended State Observer (LESO). The stability of the compound MFiPISTSMC strategy is proved by the Lyapunov stability theorem. As a result of the compound MFiPISTSMC strategy integrating the STSMC strategy, the iPI control strategy and the LESO is proposed to have excellent performance. Finally, the static characteristic, dynamic characteristic and robustness of the novel compound MFiPISTSMC strategy are verified by simulation and experimental results.
Introduction: It is significant for energy sharing to study the complementary utilization of multiple energy sources, such as water, electricity and gas, and the interaction among multiple stakeholders. Methods: We propose a research on energy sharing between distribution network and multiple systems based on the mixed game strategy and water-electric-gas integrated energy complementation. Firstly, this paper describes the relationship and functions of all stakeholders under the research framework, and establishes the mathematical model of each unit in the water-electric-gas complementary IES. Secondly, the internal roles are layered based on the relationship between stakeholders in the system. Then a non-cooperative game model for the distribution network operator and multiple subsystems is established according to the theory of Stackelberg game, and a cooperative game model for multiple subsystems is further established based on the theory of Nash bargaining. In the next step, the complexity of the problem is analyzed, followed by the description of the specific algorithm and process of solving the model. Results: Finally, the results of example analysis show that the model proposed in this paper not only balances the interests of stakeholders at the upper and lower layers of the system, but also allocates the interests of multiple subsystems at the lower layer. Discussion: Thus effectively improving the energy utilization of the system.
This paper is concerned with the non-fragile sampled data H∞ filtering problem for continuous Markov jump linear system with partly known transition probabilities (TPs).The filter gain is assumed to have additive variations and TPs are assumed to be known, uncertain with known bounds and completely unknown.The aim is to design a non-fragile H∞ filter to ensure both the robust stochastic stability and a prescribed level of H∞ performance for the filtering error dynamics.Sufficient conditions for the existence of such a filter are established in terms of linear matrix inequalities (LMIs).An example is provided to demonstrate the effectiveness of the proposed approach.
This paper proposed a novel method which is the combination of traditional cross feedback control and sliding mode control for the problem of gyroscopic coupling and imbalance disturbance in the rotor system of magnetic suspended wind turbines when they rotate under high speed situation. Firstly, the mathematical model of a radial four-degree-of-freedom active magnetic bearing rotor system is derived. Then, a sliding mode controller is designed after decoupling the model by using cross feedback control method. The stability of the whole system is guaranteed by the Lyapunov stability theory. Better robustness and regulation performance is obtained through comparing with a traditional decentralized PID-based cross feedback controller numerically.
This study proposes a novel hierarchical nonlinear proportional-integral fast terminal sliding mode (HNLPIFTSM) control for permanent magnet synchronous motor (PMSM) speed regulation system. A new type of sliding surface called HNLPIFTSM surface, which combines the benefits of a nonlinear proportional-integral (PI) sliding mode surface and a fast terminal sliding mode (FTSM) surface, is proposed to enhance the robustness and improved the dynamic response, whilst preserving the great property of the conventional hierarchical fast terminal sliding mode (HFTSM) control strategy. The proposed HNLPIFTSM surface uses the novel nonlinear PI sliding mode surface as its inner loop and uses the FTSM surface as its outer loop. Meanwhile, an extended state observer (ESO) is used to estimate the uncertain terms of the PMSM speed regulation system. Furthermore, the stability of the closed-loop control system under the ESO and the HNLPIFTSM control strategy is proved by the Lyapunov stability theorem. Finally, the simulations and experimental demonstrations verify the effectiveness and superiorities of our proposed HNLPIFTSM control strategy over the conventional HFTSM control strategy.
Abstract This paper presents a model for predicting biogas production. Most biogas production models are only suitable for laboratories due to their high complexity and are not suitable for practical production applications and promotion. The existing biogas stations have a low degree of automation, and biogas production is often manually estimated based on experience. In view of these problems, the BP neural network was studied and the biogas production prediction model was established. Genetic algorithm (GA) is introduced to optimize the model parameters to make the experimental results more accurate. The data show that the prediction effect based on GA-BP model is very ideal.
Because the gyroscopic coupling effect and the imbalance force typically generate undesirable vibrations in the rotor system of magnetic suspended wind turbines when they rotate under high speed situation, a novel cross feedback based control method is proposed. Firstly, the dynamic model of a radial four-degree-of-freedom active magnetic bearing rotor system is derived. Next, a double stage cross feedback controller is designed for suppressing the vibration caused by the gyroscopic coupling effect. Moreover, an integrator and a second order low pass filter are used to improve rotor positioning performance with disturbance. Finally, better steady accuracy and disturbance rejection performance are obtained by the proposed method through comparing with a LQR controller and a traditional cross feedback controller numerically.
A new monitoring method using distributed optical temperature measurement to measure the temperature of reactor is put forward in the paper. The paper describes the characteristics of the system, and also provides an arrangement scheme of fiber to en-sure the system running well. Good man-machine interface of the system will help staff to check the temperature easily, and send warning signal.
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