An Innovative MIMO Iterative Learning Control Approach for the Position Control of a Hydraulic Press

To improve the performance of hydraulic press position control and eliminate the need to manually define control signals, this paper proposes a multi-input-multi-output (MIMO) Iterative Learning Control (ILC) algorithm. The MIMO ILC algorithm design is based on the inversion of the known low frequency dynamics of the hydraulic press, whereas the unknown and uncertain high frequency dynamics are discarded due to their low influence in the learning transient. Moreover, for the MIMO ILC convergence condition, a graphical method is proposed, in which the ILC learning filter eigenvalues are analyzed. This method allows studying the stability and convergence rate of the algorithm intuitively. Theoretical analysis and results prove that with the MIMO ILC algorithm the position control is automated and that high precision in the position tracking is gained. A comparison with other model inverse ILC approaches is carried out and it is shown that the proposed MIMO ILC algorithm outperforms the existing algorithms, reducing the number of iterations required to converge while guaranteeing system stability. Furthermore, experimental results in a hydraulic test rig are presented and compared to those obtained with a conventional PI controllerThis work was supported in part by the Department of Development and Infrastructures of the Government of the Basque Country via Industrial Doctorate Program BIKAINTEK under Grant 20-AF-W2-2018-00015

Iterative learning control in the commissioning of industrial presses

182 p.This thesis presents solutions to the control problems that exist nowadays in industrial presses, followed by a discussion of the most appropriate control schemes that may be used for their solution. Iterative Learning Control is subsequently analyzed, as the most promising control scheme for machine presses, due to its capability to improve the performance of a system that operates repeatedly.A novel Iterative Learning Control design is presented, which makes use of the dynamic characteristics of the system to improve the current controller performance and stability. This, results in an adaptation of the presented Iterative Learning Control design to two use cases: the single-input-single-output force control of mechanical presses and the multiple-input-multiple-output position control of hydraulic presses. While existing Iterative Learning Control approaches are also described and applied to the previously mentioned use cases, the presented novel approach has been shown to outperform the existing algorithms in terms of control performance.The proposed Iterative Learning control algorithms are validated in an experimental hydraulic test rig, in which the performance, robustness and stability of the algorithm have been demonstrated

Development of Motion Control Systems for Hydraulically Actuated Cranes with Hanging Loads

Automation has been used in industrial processes for several decades to increase efficiency and safety. Tasks that are either dull, dangerous, or dirty can often be performed by machines in a reliable manner. This may provide a reduced risk to human life, and will typically give a lower economic cost. Industrial robots are a prime example of this, and have seen extensive use in the automotive industry and manufacturing plants. While these machines have been employed in a wide variety of industries, heavy duty lifting and handling equipment such as hydraulic cranes have typically been manually operated. This provides an opportunity to investigate and develop control systems to push lifting equipment towards the same level of automation found in the aforementioned industries. The use of winches and hanging loads on cranes give a set of challenges not typically found on robots, which requires careful consideration of both the safety aspect and precision of the pendulum-like motion. Another difference from industrial robots is the type of actuation systems used. While robots use electric motors, the cranes discussed in this thesis use hydraulic cylinders. As such, the dynamics of the machines and the control system designmay differ significantly. In addition, hydraulic cranes may experience significant deflection when lifting heavy loads, arising from both structural flexibility and the compressibility of the hydraulic fluid. The work presented in this thesis focuses on motion control of hydraulically actuated cranes. Motion control is an important topic when developing automation systems, as moving from one position to another is a common requirement for automated lifting operations. A novel path controller operating in actuator space is developed, which takes advantage of the load-independent flow control valves typically found on hydraulically actuated cranes. By operating in actuator space the motion of each cylinder is inherently minimized. To counteract the pendulum-like motion of the hanging payload, a novel anti-swing controller is developed and experimentally verified. The anti-swing controller is able to suppress the motion from the hanging load to increase safety and precision. To tackle the challenges associated with the flexibility of the crane, a deflection compensator is developed and experimentally verified. The deflection compensator is able to counteract both the static deflection due to gravity and dynamic de ection due to motion. Further, the topic of adaptive feedforward control of pressure compensated cylinders has been investigated. A novel adaptive differential controller has been developed and experimentally verified, which adapts to system uncertainties in both directions of motion. Finally, the use of electro-hydrostatic actuators for motion control of cranes has been investigated using numerical time domain simulations. A novel concept is proposed and investigated using simulations.publishedVersio

PID control with gravity compensation for hydraulic 6-DOF parallel manipulator

Abstract A novel model-based controller for 6 degree-of-freedom (DOF) hydraulic driven parallel manipulator considering the nonlinear characteristic of hydraulic systems-proportional plus derivative with dynamic gravity compensation controller is presented, in order to improve control performance and eliminate steady state errors. In this paper, 6-DOF parallel manipulator is described as multi-rigid-body systems, the dynamic models including mechanical system and hydraulic driven system are built using Kane method and hydromechanics methodology, the numerical forward kinematics and inverse kinematics is solved with Newton-Raphson method and close-form solutions. The model-based controller is developed with feedback of actuator length, desired trajectories and system states acquired by forward kinematics solution as the input and servovalve current as its output. The hydraulic system is decoupled by local velocity compensation in inner control loop prerequisite for the controller. The performance revolving stability, accuracy and robustness of the proposed control scheme for 6-DOF parallel manipulator is analyzed in theory and simulation. The theoretical analysis and simulation results indicate the controller can improve the control performance and eliminate the steady state errors of 6-DOF hydraulic driven parallel manipulator

Modeling and control of a modular iron bird

This paper describes the control architecture and the control laws of a new concept of Modular Iron Bird aimed at reproducing flight loads to test mobile aerodynamic control surface actuators for small and medium size aircraft and Unmanned Aerial Vehicles. The iron bird control system must guarantee the actuation of counteracting forces. On one side, a hydraulic actuator simulates the hinge moments acting on the mobile surface due to aerodynamic and inertial effects during flight; on the other side, the actuator to be tested applies an active hinge moment to control the angular position of the same surface. Reference aerodynamic and inertial loads are generated by a flight simulation module to reproduce more realistic conditions arising during operations. The design of the control action is based on a dynamic model of the hydraulic plant used to generate loads. This system is controlled using a Proportional Integral Derivative control algorithm tuned with an optimization algorithm taking into account the closed loop dynamics of the actuator under testing, uncertainties and disturbances in the controlled plant. Numerical simulations are presented to show the effectiveness of the proposed architecture and control laws