Minimum Time Control of a Gantry Crane System with Rate Constraints

This paper focuses on the development of minimum time control profiles for point-to-point motion of a gantry crane system in the presence of uncertainties in modal parameters. Assuming that the velocity of the trolley of the crane can be commanded and is subject to limits, an optimal control problem is posed to determine the bang-off-bang control profile to transition the system from a point of rest to the terminal states with no residual vibrations. Both undamped and underdamped systems are considered and the variation of the structure of the optimal control profiles as a function of the final displacement is studied. As the magnitude of the rigid body displacement is increased, the collapse and birthing of switches in the optimal control profile are observed and explained. Robustness to uncertainties in modal parameters is accounted for by forcing the state sensitivities at the terminal time to zero. The observation that the time-optimal control profile merges with the robust time-optimal control is noted for specific terminal displacements and the migration of zeros of the time-delay filter parameterizing the optimal control profile are used to explain this counter intuitive result. A two degree of freedom gantry crane system is used to experimentally validate the observations of the numerical studies and the tradeoff of increase in maneuver time to the reduction of residual vibrations is experimentally illustrated

Multi-objective Anti-swing Trajectory Planning of Double-pendulum Tower Crane Operations using Opposition-based Evolutionary Algorithm

Underactuated tower crane lifting requires time-energy optimal trajectories for the trolley/slew operations and reduction of the unactuated swings resulting from the trolley/jib motion. In scenarios involving non-negligible hook mass or long rig-cable, the hook-payload unit exhibits double-pendulum behaviour, making the problem highly challenging. This article introduces an offline multi-objective anti-swing trajectory planning module for a Computer-Aided Lift Planning (CALP) system of autonomous double-pendulum tower cranes, addressing all the transient state constraints. A set of auxiliary outputs are selected by methodically analyzing the payload swing dynamics and are used to prove the differential flatness property of the crane operations. The flat outputs are parameterized via suitable B\'{e}zier curves to formulate the multi-objective trajectory optimization problems in the flat output space. A novel multi-objective evolutionary algorithm called Collective Oppositional Generalized Differential Evolution 3 (CO-GDE3) is employed as the optimizer. To obtain faster convergence and better consistency in getting a wide range of good solutions, a new population initialization strategy is integrated into the conventional GDE3. The computationally efficient initialization method incorporates various concepts of computational opposition. Statistical comparisons based on trolley and slew operations verify the superiority of convergence and reliability of CO-GDE3 over the standard GDE3. Trolley and slew operations of a collision-free lifting path computed via the path planner of the CALP system are selected for a simulation study. The simulated trajectories demonstrate that the proposed planner can produce time-energy optimal solutions, keeping all the state variables within their respective limits and restricting the hook and payload swings.Comment: 14 pages, 14 figures, 6 table

NONLINEAR CONTROL STRATEGIES AND PLANNING FOR UNDERACTUATED OVERHEAD CRANES

Underactuated overhead cranes play an important role in engineering and construction, which also make nonlinear control strategies and planning on this basis become the current focus of academic research. Based on scholarly research findings, this paper carries out a theoretical study on nonlinear control strategies and planning for underactuated overhead cranes. To begin with, the underactuated system, underactuated overhead cranes and its nonlinear control are elucidated. Afterwards, the stabilization methods for front actuators are analyzed, and finally two nonlinear control methods are explored in the hope of providing some references for research in related fields

Control of an Underactuated Double-Pendulum Overhead Crane using Improved Model Reference Command Shaping: Design, Simulation and Experiment

This paper presents a new control scheme based on model reference command shaping (MRCS) for an overhead crane, with double-pendulum mechanism effects. The approach has an advantage in achieving an accurate trolley positioning, with low hook and payload oscillations, under various desired trolley positions and parameter uncertainties, without the requirement for measurement or estimation of system parameters. These are challenging in practice. The previously developed MRCS algorithm is improved in order to reduce its design complexity, as well as to ensure that it can be augmented with a feedback controller so that a concurrent controller tuning can be realised. The combined MRCS and feedback controller is used to achieve both, precise trolley positioning, and low hook and payload oscillations. To evaluate the effectiveness and the robustness of the approach, simulations and experiments using a nonlinear model and a laboratory double-pendulum crane are carried out. Under various desired positions and parameter uncertainties that involve varying the cable lengths (payload hoisting) and the payload mass variations, the superiority of the proposed approach is confirmed by achieving higher hook and payload oscillation reductions when compared with a recently proposed feedback controller. In addition, the desired trolley positions are achieved with smoother responses

Safe distance prediction for braking control of bridge cranes considering anti-swing

Cranes are widely deployed for lifting and moving heavy objects in dynamic environments with human coexistence. Suddenly appeared workers, vehicles, and robots can affect the safety of the cranes. To avoid possible collisions, the cranes must have prediction ability to know how dangerous the situation is. In this paper, we address the safety issues of bridge cranes based on its online physical states and control model. Due to the swing of the payload, the safe braking distance cannot be a constant value. Therefore, we here propose a model prediction control (MPC)-based anti-swing method for non-zero initial states, where a new reference trajectory and a new cost function for optimization are proposed, such that the proposed MPC method can control the crane to follow the proposed reference trajectory and achieve a stable stop state with anti-swing. Furthermore, an offline learning mechanism is introduced to learn a statistical model between the velocity of the crane and the safe braking distance achieved by using the proposed MPC braking control method. In this way, we can predict how far the crane would require to safely stop without swing based on its current velocity, which is the safe distance prediction to evaluate the dangerous level of the dynamic obstacle. Experiments using both a simulated crane and a real crane demonstrate that the proposed safe braking distance prediction method is effective for safe braking control of the bridge cranes

Advanced Discrete-Time Control Methods for Industrial Applications

This thesis focuses on developing advanced control methods for two industrial systems in discrete-time aiming to enhance their performance in delivering the control objectives as well as considering the practical aspects. The first part addresses wind power dispatch into the electricity network using a battery energy storage system (BESS). To manage the amount of energy sold to the electricity market, a novel control scheme is developed based on discrete-time model predictive control (MPC) to ensure the optimal operation of the BESS in the presence of practical constraints. The control scheme follows a decision policy to sell more energy at peak demand times and store it at off-peaks in compliance with the Australian National Electricity Market rules. The performance of the control system is assessed under different scenarios using actual wind farm and electricity price data in simulation environment. The second part considers the control of overhead crane systems for automatic operation. To achieve high-speed load transportation with high-precision and minimum load swings, a new modeling approach is developed based on independent joint control strategy which considers actuators as the main plant. The nonlinearities of overhead crane dynamics are treated as disturbances acting on each actuator. The resulting model enables us to estimate the unknown parameters of the system including coulomb friction constants. A novel load swing control is also designed based on passivity-based control to suppress load swings. Two discrete-time controllers are then developed based on MPC and state feedback control to track reference trajectories along with a feedforward control to compensate for disturbances using computed torque control and a novel disturbance observer. The practical results on an experimental overhead crane setup demonstrate the high performance of the designed control systems.Comment: PhD Thesis, 230 page

Nonlinear optimal control for the 4-DOF underactuated robotic tower crane

Tower cranes find wide use in construction works, in ports and in several loading and unloading procedures met in industry. A nonlinear optimal control approach is proposed for the dynamic model of the 4-DOF underactuated tower crane. The dynamic model of the robotic crane undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method. The linearization relies on Taylor series expansion and on the associated Jacobian matrices. For the linearized state-space model of the system a stabilizing optimal (H-infinity) feedback controller is designed. To compute the controller’s feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis. The proposed control approach is advantageous because: (i) unlike the popular computed torque method for robotic manipulators, the new control approach is characterized by optimality and is also applicable when the number of control inputs is not equal to the robot’s number of DOFs, (ii) it achieves fast and accurate tracking of reference setpoints under minimal energy consumption by the robot’s actuators, (iii) unlike the popular Nonlinear Model Predictive Control method, the article’s nonlinear optimal control scheme is of proven global stability and convergence to the optimum.This research work has been partially supported by Grant Ref. “CSP contract 040322”—“Nonlinear control, estimation and fault diagnosis for electric power generation and electric traction/propulsion systems” of the Unit of Industrial Automation of the Industrial Systems Institute

MPC-PID control of operator-in-the-loop overhead cranes: A practical approach

In this paper, a velocity control system for industrial overhead cranes based on a Model Predictive Control approach is proposed. The problem of the control of the operator-in-the-loop system is addressed, as the operator drives the system pushing a button while the control algorithm drives the cart reducing the oscillations of the load. An inner velocity control loop is used in order to overcome some of the problems of controlling the system by using directly the torque of the motor as a control variable. Simulations show the effectiveness of the approach, in particular in the presence of friction

Model Predictive Control for operator-in-the-loop overhead cranes

In this paper, a Model Predictive Control approach for the velocity control of operator-in-the loop overhead cranes is proposed. The operator can select the maximum position overshoot as a tuning parameter for the method. Simulations provide a comparison between the proposed method and the well known Zero Vibration input shaping technique, showing its effectiveness in controlling the payload oscillations

Control of an underactuated double-pendulum overhead crane using improved model reference command shaping: Design, simulation and experiment

This paper presents a new control scheme based on model reference command shaping (MRCS) for an overhead crane, with double-pendulum mechanism effects. The approach has an advantage in achieving an accurate trolley positioning, with low hook and payload oscillations, under various desired trolley positions and parameter uncertainties, without the requirement for measurement or estimation of system parameters. These are challenging in practice. The previously developed MRCS algorithm is improved in order to reduce its design complexity, as well as to ensure that it can be augmented with a feedback controller so that a concurrent controller tuning can be realised. The combined MRCS and feedback controller is used to achieve both, precise trolley positioning, and low hook and payload oscillations. To evaluate the effectiveness and the robustness of the approach, simulations and experiments using a nonlinear model and a laboratory double-pendulum crane are carried out. Under various desired positions and parameter uncertainties that involve varying the cable lengths (payload hoisting) and the payload mass variations, the superiority of the proposed approach is confirmed by achieving higher hook and payload oscillation reductions when compared with a recently proposed feedback controller. In addition, the desired trolley positions are achieved with smoother responses