Three-dimensional (3D) plant canopy structure analysis is an important part of plant phenotype studies. To promote the development of plant canopy structure measurement based on 3D reconstruction, we reviewed the latest research progress achieved using visual sensors to measure the 3D plant canopy structure from four aspects, including the principles of 3D plant measurement technologies, the corresponding instruments and specifications of different visual sensors, the methods of plant canopy structure extraction based on 3D reconstruction, and the conclusion and promise of plant canopy measurement technology. In the current research phase on 3D structural plant canopy measurement techniques, the leading algorithms of every step for plant canopy structure measurement based on 3D reconstruction are introduced. Finally, future prospects for a standard phenotypical analytical method, rapid reconstruction, and precision optimization are described.

In this paper, we first design a self-tuning distributed observer for second-order multi-agent systems which is capable of providing the estimation of the leader’s signal to various followers. We then further develop an adaptive sliding-mode controller to solve the cooperative tracking problem between leader and followers for second-order multi-agent systems subject to time-varying actuator faults and unknown external disturbances, which can ensure that the leader-following cooperative tracking errors converge to zero asymptotically. Finally, a simulation example is provided to demonstrate the effectiveness of the proposed controller. This control law offers three advantages: first, the problem of communication barriers among the leader and followers can be solved by the self-tuning distributed observer, which can calculate the observer gain online; second, a new type of adaptive sliding-mode controller is proposed by introducing a Nussbaum function; and lastly, the bounds of unknown actuator faults and unknown external disturbances can be adaptively estimated.

This paper explores the fault-tolerant cooperative control of multiagent systems, which are modeled via an uncertain leader system and multiple uncertain Euler–Lagrange systems with actuator faults. A self-adjusting observer is initially proposed to estimate the signal of the uncertain leader for different followers and compute the observer gain in real time. An adaptive fault-tolerant controller is designed based on the above observer and nonsingular fast terminal sliding mode surface. This controller estimates lumped uncertainty and ensures that tracking errors are ultimately bounded. The controller designed in this paper has the following three advantages. Firstly, the observer can estimate and transmit the leader’s state to each follower even without precise knowledge of the leader’s system matrix. Secondly, the controller is robust to actuator faults, uncertain parameters and external disturbances, the upper bounds of which can be arbitrarily large and unidentified. Thirdly, the controller has a simple structure and is also suitable for situations where the actuator is healthy. Lastly, simulations are provided to demonstrate the effectiveness of both the observer and the controller with or without actuator fault.