This article considers the model predictive control (MPC) problem for a class of time-varying systems subject to both disturbances and constraints of states as well as input. Instead of directly negating disturbance by its estimation in feedback control, we exploit the disturbance estimation in the MPC optimization problem for seeking the optimal control input. In particular, the extended state observer (ESO) is constructed to obtain the disturbance estimation to be incorporated into the prediction model. Furthermore, less conservative tightened constraints and terminal constraints with consideration of disturbance estimation are constructed to guarantee robust constraint satisfaction and recursive feasibility. Also, the input-to-state stability (ISS) of the closed-loop system is rigorously proven. Finally, the proposed method is applied to the liquid-level control system. The experimental results demonstrate the effectiveness of our MPC algorithm.

The three-phase dual active bridge (DAB3) converter achieves the bidirectional power transmission and voltage conversion in DC power grid. However, DAB3 is susceptible to switch open circuit fault (SOCF), causing transmission power loss and excessive current stress. Thus, a path-based fault-tolerant method (PFTM) for SOCF in DAB3 is proposed. Firstly, the transferred energy of each phase is investigated by modality analysis of DAB3, thus, a path energization method is proposed for PFTM, and switching pattern reconfiguration strategy is summarized by switching functions during SOCF, enlarging maximum transmission power within maximum HFL inductor current. Moreover, in the PFTM, the fault paths/legs are employed, reconfiguring the current path of modality, actively adjusting the ON-time of antiparallel diode, realizing the bidirectional transmission power improvement. Furthermore, the optimization strategy of phase shift ratio is proposed to reduce high-frequency-link (HFL) current stress and keep zero-voltage switching (ZVS), when SOCF is in primary and secondary sides. Compared with traditional methods, the PFTM can realize a wider power range and voltage gain, and a higher maximum transmission power, to ensure the safety and reliability of DAB3. Finally, experimental results verify the theoretical analysis.

With the increasing penetration of renewable energy sources in power systems, the distributed optimal control (DOC) method has been regarded as an effective way to integrally solve the load frequency control and economic dispatch problem in real time. This article proposes a novel DOC method to deal with the nonlinear characteristics of cyber–physical power systems including physical constraints and time delay. First, based on the integration of the partial primal–dual gradient algorithm and active disturbance rejection control method, this article develops an active disturbance rejection control (ADRC) based DOC method to improve frequency control performance. Then, the positive projection operators are introduced into the ADRC-based DOC method to realize the generation saturation constraints and thermal limits of tie-lines. The stability is theoretically proved by the Lyapunov function. Furthermore, a delay-compensated extended state observer is designed and used to rederive the DOC method to deal with both physical constraints and time delay. Finally, numeral results are obtained with a real-time hardware-in-loop experiment platform and analyzed to verify the effectiveness of the proposed method.

This study discusses the influence of natural wind on the air flow of air-cooled condensers (ACCs) and then proposes a partition speed-regulation strategy for a fan group with enhanced generalized capability, which is of great practical significance for optimizing energy-saving operations. The stochastic time-varying features of natural wind are characterized by sine–Gaussian, Weibull, and composed winds. In a natural wind disturbance, using the Sugon Supercomputing Center, the transient numerical simulation of the dynamic evolution of the ACC flow field was found: the dynamic system of air flow is a typical time-varying nonlinear process. Cluster analysis was used to extract the nonlinear features of air flow, divide the fan group into four subregions with generalization capability, and implement a partitioned speed operation. It was found that giving priority to increasing the fan speed in the headwind partition can suppress the natural wind disturbance and improve the overall air flow, thus reducing the fan speed in the leeward partition, which reduces the overall air flow loss. The dynamic characteristics of the fan group obtained from the simulation and the proposed fan partition method can guide the optimized energy-saving operation of ACCs.