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Abstract The leaves above the ear serve as a major source of carbohydrates for grain filling in maize. However, increasing the number of leaves above the ear to strengthen the source and improve maize yield remains challenging in modern maize breeding. Here, we clone the causative gene of the quantitative trait locus (QTL) associated with the number of leaves above the ear. The causative gene is the previously reported MADS-box domain-encoding gene Tunicate1 (Tu1), which is responsible for the phenotype of pod corn or Tunicate maize. We show that Tu1 can substantially increase the leaf number above the ear while maintaining the source‒sink balance. A distal upstream 5-base pair (bp) insertion of Tu1 originating from a popcorn landrace enhances its transcription, coregulates its plastochron activators and repressors, and increases the number of leaves above the ear. Field tests demonstrate that the 5-bp insertion of Tu1 can increase grain yields by 11.4% and 9.5% under regular and dense planting conditions, respectively. The discovery of this favorable Tu1 allele from landraces suggests that landraces represent a valuable resource for high-yield breeding of maize.

Unlike the other domesticated maize, sweet maize and popcorn retain tillering growth habit, but the underlying mechanism is unknown. Here, the authors identify a transcription factor tin1 that maintains outgrowth of tiller independent of tb1 and show its conservation in foxtail millet and rice.

This paper focuses on the control problem of wind energy conversion systems (WECSs) with direct-driven permanent magnet synchronous generator (PMSG) working in variable power output stage. A novel compound control scheme combined the active disturbance rejection controller (ADRC) and speed sensorless technology is proposed. In order to achieve maximum power point tracking (MPPT), a speed control loop is designed based on ADRC to improve the speed tracking ability and anti-disturbance ability of system. Moreover, considering the large amount of system model information, a model-assisted ADRC is designed on the nominal ADRC to improve the response speed of system and reduce the energy consumption for the system control. Additionally, to solve the contradiction between the requirement of speed sensor precision and the economy of system design, a speed observer based on current model is designed in α - β coordinate system. Furthermore, a resistance observer is introduced to improve the convergence rate of the observer. And a position sensorless observer structure based on the speed observer is proposed. Finally, simulation studies are conducted to evaluate power tracking performances of the proposed speed-observer-based model assisted ADRC technology. It is shown that the proposed compound scheme exhibits significant improvements in both control performance and anti-disturbance ability with high observation precision compared with the normal ADRC method.

Considering the problems of internal and external disturbances, i.e. time-varying load, inaccurate system model and external uncertainties etc., a compound control strategy based on model predictive control (MPC) and non-linear extended state observer (ESO) are proposed to attenuate the output voltage fluctuation under continuous conduction mode (CCM) mode of the buck circuits. In addition, a non-linear ESO is used to observe all kinds of uncertainties caused by internal and external disturbances and to eliminate their effects by compensating these disturbances in the feed-forward channel. Compared with the pure MPC control, the simulation results show that the proposed composite control method has the better disturbance suppression effect and also can effectively improve the stability of the buck circuit.

In this paper, a wind-turbine active power control strategy is proposed from the cluster level to optimize the active power set-point for each wind turbine in a specific cluster. The wind turbine power tracking characteristic is described as an inertial link to establish the power tracking predictive model, and the model predictive control (MPC) method is used to optimize the cluster power demand and output. Time-varying constraints are proposed to coordinate the power output for different time-scale wind turbines and sustain that the cluster has enough fast-tracking capacity when the cluster power demand changes. Under different scenarios, the proposed strategy is tested to verify the effectiveness in improving the power output stability and frequency support ability.

In wind turbine control, maximum power point tracking (MPPT) control is the main control mode for partial-load regimes. Efficiency potentiation of energy conversion and power smoothing are both two important control objectives in partial-load regime. However, on the one hand, low power fluctuation signifies inefficiency of energy conversion. On the other hand, enhancing efficiency may increase output power fluctuation as well. Thus the two objectives are contradictory and difficult to balance. This paper proposes a flexible MPPT control framework to improve the performance of both conversion efficiency and power smoothing, by adaptively compensating the torque reference value. The compensation was determined by a proposed model predictive control (MPC) method with dynamic weights in the cost function, which improved control performance. The computational burden of the MPC solver was reduced by transforming the cost function representation. Theoretical analysis proved the good stability and robustness. Simulation results showed that the proposed method not only kept efficiency at a high level, but also reduced power fluctuations as much as possible. Therefore, the proposed method could improve wind farm profits and power grid reliability.

This paper addresses the finite-time bounded control problem of linear stochastic systems with state, control input, and external disturbance-dependent noise ((x,u,v)-dependent noise for short). The notion of finite-time boundedness of linear stochastic systems is first introduced. Then a different quadratic function approach is proposed to give a sufficient condition for finite-time boundedness of such a class of systems, and its superiority to common quadratic approach is shown. Moreover, the finite-time bounded controller design problem is studied and two sufficient conditions for the existence of state and output feedback controllers are presented in terms of nonlinear matrix inequalities. An algorithm is given for solving the obtained nonlinear matrix inequalities. Finally, an example is employed to illustrate the effectiveness of our obtained results.