The study on SMC for underactuated systems still remains quite open since it is very challenging to construct a proper manifold which can simultaneously stabilize both actuated and unactuated system states. Motivated to promote the corresponding research, we propose an improved second-order SMC (IS-SMC) method for a class of nonlinear underactuated systems in this paper, which guarantees that the closed-loop system's equilibrium point is asymptotically stable even in the presence of unknown non-diminishing disturbances. Different from traditional SMC methods presenting with chattering problem, the control inputs of the proposed method are essentially continuous, which brings much convenience for practical applications. Moreover, for the disturbances which are second order differentiable, an enhanced IS-SMC (EIS-SMC) method is derived to guarantee the smoothness for both the control inputs and their derivatives. Finally, the proposed approach is applied to an overhead crane system, with sufficient simulation results provided to validate the efficiency of the proposed method.

Offshore cranes often work in harsh sea conditions. As a result, they may suffer from various external disturbances, especially the persistent and unpredictable ship motion caused by sea waves, which will introduce severe disturbances to the crane dynamics, including the unactuated part. Due to this reason, the control problem for offshore boom cranes presents great challenges, for which only boundedness or stability, instead of the generally desired asymptotic stability, of the closed-loop system can be usually guaranteed by currently available methods. For this problem, a novel nonlinear control strategy for an offshore crane is proposed in this brief, which ensures that the closed-loop system's equilibrium point is asymptotically stable even in the presence of the persistent ship roll disturbances. The proposed control law is further extended to be an output feedback controller to deal with the situations when the velocities are unavailable, still guaranteeing asymptotic stability. Finally, some experimental results are provided to validate the efficiency of the proposed controllers.

In practical applications, offshore cranes are widely utilized on large scale ships to accomplish the tasks of transferring cargos from one ship to another or between ships and harbors. Compared with traditional land-fixed cranes, offshore cranes work in noninertial (ship) frames and their movements are significantly influenced by such complicated disturbances as sea waves, etc. Hence, the control issue of offshore cranes presents much more challenges. At present, existing controllers for offshore cranes are designed based upon linearized dynamics, and they need the accurate values of the plant parameters. However, the values of the parameters, including cargo/jib masses, are usually difficult to measure or even unknown, which makes exact gravitational force compensation difficult and unavoidably results in positioning errors for luffing and hoisting/lowering control. To deal with these practical issues, we suggest a novel model-parameter-free control approach to achieve effective control for underactuated offshore crane systems. By constructing an elaborate storage function, we provide a complete Lyapunov-based stability analysis. As far as we know, this paper provides the first control strategy to asymptotically regulate an offshore crane system subject to parametric uncertainties and ship-induced perturbations, which is developed without simplifying the original nonlinear dynamic equations. At last, a series of experimental results, carried out on a self-built offshore crane hardware platform, are presented to validate the effectiveness and robustness of the presented control scheme.

In this article, a novel robust observer-based nonlinear control approach is proposed for quadrotors with unmodeled dynamics and external disturbances, wherein the tracking errors are restricted effectively. Two nonlinear disturbance observers are proposed to deal with uncertainties in the inner and outer loops, respectively. On this basis, a robust observer-based nonlinear control approach is put forward for quadrotor systems. Specifically, in the outer loop subsystem, a robust observer-based control scheme is proposed, which can reduce unexpected tracking errors for quadrotors effectively. Subsequently, based upon the geometric methods, the coordinate-free attitude controller and the nonlinear disturbance observer are integrated as a robust controller in the inner loop subsystem. Based upon full nonlinear dynamics, the solutions of the closed-loop system are proven to be uniformly ultimately bounded by means of rigorous Lyapunov analysis. A series of comparative experiments consisting of the implementation of a nonlinear proportional-integral-derivative (PID)-type controller, an observer-based sliding mode controller, and the proposed controller are conducted to demonstrate the remarkable performance of the proposed method in terms of higher tracking accuracy and stronger robustness.

In practical applications, boom cranes are widely used as useful transportation tools in various fields, owing to such advantages as high flexibility, good mobility, strong operability, etc. A boom crane presents complicated dynamical characteristics mainly due to its complex multidimensional movements as well as payload swings. In this paper, a new nonlinear controller is proposed for boom cranes. Specifically, the control scheme can achieve two dimensional rotary positioning and swing suppression simultaneously, with an additional coupling term and an overshoot-limiting term being incorporated to increase the transient performance. Consequently, the asymptotic stability is proven by utilizing Lyapunov techniques. To the best of our knowledge, the proposed approach is the first closed-loop control method to solve the positioning and anti-oscillation problem for 3-dimensional boom cranes without linearizing the original nonlinear dynamics for controller design or analysis. Finally, hardware experimental results are presented to demonstrate the efficiency of the proposed control method.

In this letter, we propose a tightly coupled LiDAR-inertial-visual (LIV) state estimator termed LIVER, which achieves robust and accurate localization and mapping in underground environments. LIVER starts with an effective strategy for LIV synchronization. A robust initialization process that integrates LiDAR, vision, and IMU is realized. A tightly coupled, nonlinear optimization-based method achieves highly accurate LiDAR-inertial-visual odometry (LIVO) by fusing LiDAR, visual, and IMU information. We consider scenarios in underground environments that are unfriendly to LiDAR and cameras. A visual-IMU-assisted method enables the evaluation and handling of LiDAR degeneracy. A deep neural network is introduced to eliminate the impact of poor lighting conditions on images. We verify the performance of the proposed method by comparing it with the state-of-the-art methods through public datasets and real-world experiments, including underground mines. In underground mines test, tightly coupled methods without degeneracy handling lead to failure due to self-similar areas (affecting LiDAR) and poor lighting conditions (affecting vision). In these conditions, our degeneracy handling approach successfully eliminates the impact of disturbances on the system.