Anti-sway method for reducing vibrations on a tower crane structure

We develop a solution to the problem of the behavior of a tower crane considered as a deformable system, and therefore subject to vibrations, whereas the controlled movement of a payload is implemented. The motion of the payload is calculated taking into account the normal vibration modes of the tower crane and the swaying of the payload. A “command smoothing” method relative to an open-loop system is used for reducing the sway of the payload, through smoothing the original command by the crane operator. This leads, as a consequence, to a reduction in the vibrations of the crane structure. An iterative calculation of the sway angle and the corresponding applied velocity profiles as input to the crane motors is applied. The tower crane is considered as a high nonlinear underactuated system; it is modeled considering the possible deformation of the structure. The results relating to the normal deformations of the crane are obtained, highlighting how these vibrations are strongly attenuated when an anti-sway system for the payload is implemented. Therefore, it is shown how this control leads to the best results in terms of performance for both the payload movement (shortest possible profile for the rotation movement and damping of the load oscillation) and the structure of the tower crane. Applying the method described in this paper, the structure of the tower crane does not undergo the strong horizontal and vertical oscillations that occur when the elastic structure is not considered in the crane model.

Variable-time-interval trajectory optimization-based dynamic walking control of bipedal robot

Bipedal robots by their nature show both hybrid and underactuated system features which are not stable and controllable at every point of joint space. They are only controllable on certain fixed equilibrium points and some trajectories that are periodically stable between these points. Therefore, it is crucial to determine the trajectory in the control of walking robots. However, trajectory optimization causes a heavy computational load. Conventional methods to reduce the computational load weaken the optimization accuracy. As a solution, a variable time interval trajectory optimization method is proposed. In this study, optimization accuracy can be increased without additional computational time. Moreover, a five-link planar biped walking robot is designed, produced, and the dynamic walking is controlled with the proposed method. Finally, cost of transport (CoT) values are calculated and compared with other methods in the literature to reveal the contribution of the study. According to comparisons, the proposed method increases the optimization accuracy and decreases the CoT value.

Adaptive neural network control of second-order underactuated systems with prescribed performance constraints

This paper studies the trajectory tracking control problem of second-order underactuated system subject to system uncertainties and prescribed performance constraints. By combining radial basis function neural networks (RBFNNs) with input–output linearization methods, an adaptive neural network-based control approach is proposed and the adaptive laws are given through Lyapunov method and Taylor expansion linearization approach. The main contributions of this paper are that: (1) by introducing weight performance function and transformation function, the states never violate the prescribed performance constraints; (2) the control scheme takes the unknown control gain direction into consideration and the singular problem of control design can be avoided; (3) through rigorously stability analysis, all signal of closed-loop system are proved to be uniformly ultimately bounded. The effectiveness of the proposed control scheme was verified by comparative simulation.

Neural Network Control for Trajectory Tracking and Balancing of a Ball-Balancing Robot with Uncertainty

In this paper, a neural-network-based control method to achieve trajectory tracking and balancing of a ball-balancing robot with uncertainty is presented. Because the ball-balancing robot is an underactuated system and has nonlinear couplings in the dynamic model, it is challenging to design a controller for trajectory tracking and balancing. Thus, various approaches have been proposed to solve these problems. However, there are still problems such as the complex control system and instability. Therefore, the objective of this paper was to propose a solution to these problems. To this end, we developed a virtual angle-based control scheme. Because the virtual angle was used as the reference angle to achieve trajectory tracking while keeping the balance of the ball-balancing robot, we could solve the underactuation problem using a single-loop controller. The radial basis function networks (RBFNs) were employed to compensate uncertainties, and the controller was designed using the dynamic surface control (DSC) method. From the Lyapunov stability theory, it was proven that all errors of the closed-loop control system were uniformly ultimately bounded. Therefore, the control system structure was simple and ensured stability in achieving simultaneous trajectory tracking and balancing of the ball-balancing robot with uncertainty. Finally, the simulation results are given to verify the performance of the proposed controller through comparison results. As a result, the proposed method showed a 19.2% improved tracking error rate compared to the existing method.

A New Stabilization Algorithm for Mechanical Systems with Underactuation Degree One based on Controlled Lagrangians

A new stabilization control algorithm based on controlled Lagrangian method for a class of mechanical systems with underactuation degree one is presented in this paper. Firstly, a desired controlled system with the Lagrangian structure and desired properties is constructed. By equating the underactuated system with the desired system, the matching condition and controller structure are determined. A sufficient condition for the matching condition to be held is derived, and from the sufficient condition desired kinetic energy, potential energy, gyroscopic forces and dissipative forces of the desired system can be solved explicitly. Compared with the existing matching conditions, to solve proposed sufficient condition at most two partial differential equations needs to be solved, and the rests are all algebraic equations, which is easier to solve. An algorithm to solve this sufficient condition is given in detail, and a nonlinear smooth feedback control law can be obtained to stabilize the underactuated systems. Finally, the novel control algorithm is applied to achieve almost global stability for a vertical takeoff and landing aircraft and to locally stabilize a Pendubot with two degrees of freedom at the highest point. Simulation results demonstrate effectiveness of the proposed method.

Cascade control for heterogeneous multirotor UAS

PurposeDespite of the numerous characteristics of the multirotor unmanned aircraft systems (UASs), they have been termed as less energy-efficient compared to fixed-wing and helicopter counterparts. The purpose of this paper is to explore a more efficient multirotor configuration and to provide the robust and stable control system for it.Design/methodology/approachA heterogeneous multirotor configuration is explored in this paper, which employs a large rotor at the centre to provide majority of lift and three small tilted booms rotors to provide the control. Design provides the combined characteristics of both quadcopters and helicopters in a single UAS configuration, providing endurance of helicopters keeping the manoeuvrability, simplicity and control of quadcopters. In this paper, rotational as well as translational dynamics of the multirotor are explored. Cascade control system is designed to provide an effective solution to control the attitude, altitude and position of the rotorcraft.FindingsOne of the challenging tasks towards successful flight of such a configuration is to design a stable and robust control system as it is an underactuated system possessing complex non-linearities and coupled dynamics. Cascaded proportional integral (PI) control approach has provided an efficient solution with stable control performance. A novel motor control loop is implemented to ensure enhanced disturbance rejection, which is also validated through Dryden turbulence model and 1-cosine gust model.Originality/valueRobustness and stability of the proposed control structure for such a dynamically complex UAS configuration is demonstrated with stable attitude and position performance, reference tracking and enhanced disturbance rejection.