Combined input shaping and feedback control for double-pendulum systems

Mar, Robert; Goyal, Akshit; Nguyen, Vinh; Yang, Tianle; Singhose, William

doi:10.1016/j.ymssp.2016.08.012

Cited by 76 publications

(39 citation statements)

References 24 publications

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“…Feedback control methods [8,9] utilize measurements of the system in reducing the payload swing whereas feedforward approaches work by altering the actuator commands so that system's vibration is suppressed. One of the useful approaches for reducing motion-induced vibration in underactuated systems is input shaping.…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

“…According to (8), the acceleration curve of the trolley directly impacts the residual swing of the payload. Generating an appropriate acceleration curve for a trolley can help to suppress the residual swing of the payload.…”

Section: Using the Bezier Curve To Generate Trolley Accelerationmentioning

confidence: 99%

“…The Bezier curve is generated as the trolley displacement and trolley acceleration can be calculated according to its displacement as in (9) and (11). Meanwhile, the residual swing of the payload is calculated by the trolley's acceleration according to (8). In other words, the residual swing of the payload is a function of the control points ( 0 , 1 , ⋅ ⋅ ⋅ , ), which can be defined as ( 0 , 1 , ⋅ ⋅ ⋅ , ), and the residual swing of the payload can be suppressed through generating suitable control points on the Bezier curve.…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

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Using the Bezier Curve and Particle Swarm Optimization in Trajectory Planning for Overhead Cranes to Suppress the Payloads’ Residual Swing

Liu

2018

Mathematical Problems in Engineering

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An overhead crane is an underactuated system, which leads to residual swing of the crane’s payload when the crane accelerates or decelerates. This paper proposes a trajectory planning approach which uses the Bezier curve and particle swarm optimizer (PSO-BC) to limit the residual swing of a payload. The dynamic equation for an overhead crane is discredited, and a five-order Bezier curve is generated as the trolley’s displacement. The trolley’s desired position is set as the last control point of the Bezier curve, which guarantees that the trolley reaches the desired position accurately. Various constraints, including restricting the swing angle, the allowable trolley velocity, and the allowable trolley acceleration, are then taken into consideration as the constraints. In order to make the trolley reach its desired position whilst suppressing the payload’s swing under the constraints, a particle swarm optimizer is used to determine the optimal control point positions of the Bezier curve. Finally, the PSO-BC simulation results are compared to some existing approaches and are presented to show the feasibility and robustness of the proposed PSO-BC method. The simulation results indicate that the trolley moved to the desired position accurately whilst the payload’s swing angle is kept to an allowable level.

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Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Section: Using the Bezier Curve To Generate Trolley Accelerationmentioning

confidence: 99%

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

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Using the Bezier Curve and Particle Swarm Optimization in Trajectory Planning for Overhead Cranes to Suppress the Payloads’ Residual Swing

Liu

2018

Mathematical Problems in Engineering

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“…With input shaping, an input reference command is convolved with a sequence of strictly calculated impulses, called input shaper, to produce a shaped command to suppress vibration. However, only the asymptotic convergence and vibration suppression can be guaranteed at present . Moreover, the actuator faults, external disturbances, and unavailable angular velocity are rarely considered simultaneously when the IS is used to suppress vibration.…”

Section: Introductionmentioning

confidence: 99%

“…However, only the asymptotic convergence and vibration suppression can be guaranteed at present. 44,45 Moreover, the actuator faults, external disturbances, and unavailable angular velocity are rarely considered simultaneously when the IS is used to suppress vibration.…”

Section: Introductionmentioning

confidence: 99%

Continuous robust fault‐tolerant control and vibration suppression for flexible spacecraft without angular velocity

Zhang

Zong

Tian

et al. 2019

Intl J Robust & Nonlinear

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Summary The fault‐tolerant control and vibration suppression for flexible spacecraft without angular velocity measurement are investigated. External disturbances, actuator faults, unknown angular velocity, and flexible vibration are addressed simultaneously. Firstly, a model‐free adaptive supertwisting state observer and an angular velocity calculation algorithm in one step are developed by using attitude information only, which can estimate the angular velocity in finite time. Then, on the basis of angular velocity estimation, a novel continuous multivariable integral sliding mode (CMISM) is proposed for the first time, which is a combination of continuous nominal controller and a modified multivariable twisting controller to reject disturbances and faults. The CMISM can stabilize attitudes in finite time and attenuate chattering effectively. Furthermore, the input shaping technique is developed to achieve effective vibration suppression of the flexible appendages. Finally, the efficiency of the proposed method is illustrated by numerical simulations.

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A pure neural network controller for double‐pendulum crane anti‐sway control: Based on Lyapunov stability theory

Chen

Gao

et al. 2019

Asian Journal of Control

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Crane systems have been widely applied in logistics due to their efficiency of transportation. The parameters of a crane system may vary from each transport, therefore the anti-sway controller should be designed to be insensitive to the variation of system parameters. In this paper, we focus on pure neural network adaptive tracking controller design issue that does not require the parameters of crane systems, i.e. the trolley mass, the payload mass, the cable lengths, and etc. The proposed neural network controller only requires the output feedback signals of the trolley, i.e. the position and the velocity, which means no sway measuring equipment is needed. The Lyapunov method is utilized to design the weights update law of neural network, and the robustness of the proposed controller is proved by the Lyapunov stability theory. The results of numerical simulations show that the proposed neural network controller has excellent performance of trolley position tracking and payload anti-sway controlling. KEYWORDS adaptive control, anti-sway control, double-pendulum crane systems, Lyapunov stability theory, neural network control 1 | INTRODUCTION Crane systems with cable hoisting mechanism are typically under-actuated systems. They play an important role in logistics and are widely used in container harbors, railway container yards, and other industrial factories. As cable hoisting mechanism is adopted, the weight of the crane is reduced, but the payload swings unavoidably during the transportation as well as reaching the desired position. The sway of the payload decreases the efficiency of crane's transportation and may result in hazards, such as collision, tip over, and etc. To improve the effectiveness and the safety of crane, researchers proposed many anti-sway control strategies to position the trolley accurately and eliminate the payload sway. All the anti-sway control strategies aim to: i) move the trolley safely, fast, and accurately to the desired position, and ii) decrease the sway of the payload as much as possible during the transportation and eliminate the residual sway when reaching the desired position. TIf the parameters of crane systems are exactly known, open-loop control strategies can work effectively. Singhose et al. reviewed the command shaping/input shaping [1] and implemented the method on doublependulum crane systems [2,3]. It shows that the method

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Combined input shaping and feedback control for double-pendulum systems

Cited by 76 publications

References 24 publications

Using the Bezier Curve and Particle Swarm Optimization in Trajectory Planning for Overhead Cranes to Suppress the Payloads’ Residual Swing

Using the Bezier Curve and Particle Swarm Optimization in Trajectory Planning for Overhead Cranes to Suppress the Payloads’ Residual Swing

Continuous robust fault‐tolerant control and vibration suppression for flexible spacecraft without angular velocity

A pure neural network controller for double‐pendulum crane anti‐sway control: Based on Lyapunov stability theory

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