Janne Koivumäki

The automation of multi degree of freedom hydraulic crane by using Virtual Decomposition Control

In this paper heavy-duty hydraulic crane automation is addressed by applying the Virtual Decomposition Control (VDC) approach. The VDC approach allows the control problem of the entire system to be converted into the control problem of individual components, i.e. subsystems while rigorously guaranteeing the stability of the entire system without jeopardizing the control performance. The experimental results demonstrate that the VDC approach is applicable to robust and high performance control of low-cost hydraulic multi Degree of Freedom (DOF) applications, in which the controller is challenged by a significant number of different nonlinearities and parameter uncertainties. When a VDC controller was compared with a conventional PID controller, approximately 7 times lower piston position maximum error was achieved. Moreover, a VDC controller was given roughly the same control accuracy with low, medium and high velocity trajectory references without any additional tuning, whereas the performance of the PID controller significantly changed between different velocity trajectories. The achieved results with the VDC controller are comparable with the reported state-of-the-art studies on nonlinear model-based control of hydraulic multi DOF applications.

An energy-efficient high performance motion control of a hydraulic crane applying virtual decomposition control

Hydraulic actuators are well-known for their high power-to-weight ratio, rapid responses, compactness and reliable performance. However, one of the drawbacks of fluid power systems have been large energy losses. In this paper, our research objective is to develop both energy-efficient and high performance motion controller for heavy-duty hydraulic manipulators. We apply an unconventional Servo Meter-In Meter-Out (SMIMO) hydraulic valve control setup that is used to decouple hydraulic actuator load pressure level from load force to improve energy efficiency. The developed control system is based on the Virtual Decomposition Control (VDC) approach to guarantee the closed-loop system stability of the multi degree of freedom heavy-duty hydraulic crane driven by the proposed novel SMIMO VDC controller. Capability for approximately 42% lower energy consumption was achieved in the Cartesian motion trajectory experiments with the proposed novel controller compared with a conventional 4-way servo valve setup, without significant control performance deterioration.

Hydraulic manipulator virtual decomposition control with performance analysis using low-cost MEMS sensors

This paper presents closed-loop motion control of a heavy-duty hydraulic manipulator using non-linear model-based Virtual Decomposition Control (VDC), where the motion feedback is estimated solely with low-cost micro-electromechanical systems (MEMS) inertial sensors. By virtually decomposing the strongly non-linear and dynamically cross-coupled manipulator system into individually controlled subsystems, a significant improvement in overall control performance is achieved. The controller performance is analysed using planar Cartesian end-effector motion. The experiments show that the stability-guaranteed VDC approach based on low-cost MEMS sensor feedback yields a high-performance control solution: with a 0.85 m/s maximum velocity, the end-effector has a peak tracking error of 13 mm, which is a notable improvement by a factor of 3.6 compared to our previous work based on linear state feedback control.

Geometry-aided low-noise angular velocity sensing of rigid-body manipulator using MEMS rate gyros and linear accelerometers

We consider low-noise angular velocity estimation for serial link manipulators using inertial readings from rate gyros and linear accelerometers. The research is founded on microelectromechanical systems (MEMS) components, which offer an attractive alternative to many traditional angular sensors due to their low cost, low power requirements, small size, and straightforward “strap-down” installation. By using a multi-MEMS configuration, an algebraic estimate of angular acceleration, where low- and high frequency perturbations are mostly proportional to the physical distances of linear accelerometers, is fused with rate gyro readings with the well-known principles of complementary and Kalman filtering. Experiments on a robotic three-link planar arm rig and a hydraulic heavy-duty manipulator demonstrate the feasibility of our practically lag-free novel approach.