Pumped storage power plants are key components to stabilize electric distribution networks with high amount of intermittent power sources as, e.g., solar and wind power plants. Tailored mathematical ...models are important for the transient and the stationary analysis of such plants. A comprehensive mathematical model of a variable speed operated pumped storage power plant, which incorporates reversible pump turbines in combination with doubly fed induction machines, is developed in this paper. Special emphasis is laid on an accurate description of important dynamic effects (e.g., water hammer) and of the energy losses of the system. Based on this model, optimal stationary operating points are determined, which minimize the overall system losses and systematically take into account the operating constraints.
•A comprehensive model of a variable speed pumped storage power plant is derived.•Electric and hydraulic components are taken into account.•A stationary optimization problem for minimal energy losses is formulated.•Operating constraints are systematically considered in the optimization problem.•Optimal operating points are calculated for different operating scenarios.
Vehicle dynamics control (VDC) systems require information about system variables, which cannot be directly measured, e.g. the wheel slip or the vehicle side-slip angle. This paper presents a new ...concept for the vehicle state estimation under the assumption that the vehicle is equipped with the standard VDC sensors. It is proposed to utilise an unscented Kalman filter for estimation purposes, since it is based on a numerically efficient nonlinear stochastic estimation technique. A planar two-track model is combined with the empiric Magic Formula in order to describe the vehicle and tyre behaviour. Moreover, an advanced vertical tyre load calculation method is developed that additionally considers the vertical tyre stiffness and increases the estimation accuracy. Experimental tests show good accuracy and robustness of the designed vehicle state estimation concept.
In this paper, a novel type of impedance controllers for flexible joint robots is proposed. As a target impedance, a desired stiffness and damping are considered without inertia shaping. For this ...problem, two controllers of different complexity are proposed. Both have a cascaded structure with an inner torque feedback loop and an outer impedance controller. For the torque feedback, a physical interpretation as a scaling of the motor inertia is given, which allows to incorporate the torque feedback into a passivity-based analysis. The outer impedance control law is then designed differently for the two controllers. In the first approach, the stiffness and damping terms and the gravity compensation term are designed separately. This outer control loop uses only the motor position and velocity, but no noncollocated feedback of the joint torques or link side positions. In combination with the physical interpretation of torque feedback, this allows us to give a proof of the asymptotic stability of the closed-loop system based on the passivity properties of the system. The second control law is a refinement of this approach, in which the gravity compensation and the stiffness implementation are designed in a combined way. Thereby, a desired static stiffness relationship is obtained exactly. Additionally, some extensions of the controller to viscoelastic joints and to Cartesian impedance control are given. Finally, some experiments with the German Aerospace Center (DLR) lightweight robots verify the developed controllers and show the efficiency of the proposed control approach.
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•A mathematical model for a hot strip tandem mill is developed and validated.•A new optimization-based feedforward thickness controller is developed.•A tailored numerically efficient ...solution of the optimization problem is presented.•Simulation scenarios demonstrate the performance improvement of the proposed control concept.•Promising results are obtained from a first installation of the control concept in the industrial plant.
A new feedforward control approach for the thickness profile of the strip in a tandem hot rolling mill is developed. In industry, the automatic gauge control (AGC) concept is widely used for thickness control. The AGC has the disadvantage that it does not consider known disturbances from upstream entities. This is why a number of disturbance feedforward control concepts have been proposed in the literature. These feedforward control strategies typically rely on linearized models and only provide symmetric control inputs for the mean thickness to the hydraulic adjustment system. In this work, an optimization-based feedforward controller for the lateral thickness profile is proposed that fully exploits all degrees of freedom available, i.e., the hydraulic cylinder positions and the bending forces at the drive side and at the operator side of the mill stand. Moreover, it is shown that by linearizing the mill stand model while keeping the nonlinearities from the roll gap model leads to a numerically efficient optimization problem, which is a good compromise between accuracy and computational efficiency. The feedforward controllers are further combined with the AGC in the feedback path in a two-degree-of-freedom controller structure to account for model-plant mismatch. Simulation results for a validated mathematical model and first experimental results from an industrial pilot installation show a significant benefit compared to the existing AGC without feedforward control.
Continuous strip annealing furnaces are complex multi-input multi-output nonlinear distributed-parameter systems. They are used in industry for heat treatment of steel strips. The product portfolio ...and different materials to be heat-treated is steadily increasing and the demands on high throughput, minimum energy consumption, and minimum waste have gained importance over the last years. Designing a furnace control concept that ensures accurate temperature tracking under consideration of all input and state constraints in transient operations is a challenging task, in particular in view of the large thermal inertia of the furnace compared to the strip. The control problem at hand becomes even more complicated because the burners in the different heating zones of the considered furnace can be individually switched on and off. In this paper, a real-time capable optimization-based hierarchical control concept is developed, which consists of a static optimization for the selection of an operating point for each strip, a trajectory generator for the strip velocity, a dynamic optimization routine using a long prediction horizon to plan reference trajectories for the strip temperature as well as switching times for heating zones, and a nonlinear model predictive controller with a short prediction horizon for temperature tracking. The mass flows of fuel and the strip velocity are the basic control inputs. The underlying optimization problems are transformed to unconstrained problems and solved by the Gauss–Newton method. The performance of the proposed control concept is demonstrated by an experimentally validated simulation model of a continuous strip annealing furnace at voestalpine Stahl GmbH, Linz, Austria.
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Large-scale manipulators, such as the boom of a mobile concrete pump, typically rely on lightweight construction to maximize their operational range. As a result, significant elastic deformations ...occur during operation. Various automation and control applications require computationally fast and accurate mathematical models of the manipulator's motion. In this work, a mathematical model for the boom of a mobile concrete pump with 5 individual joints is presented. This model takes into account the elastic bending in two directions and the torsion of the boom. To reach a high model accuracy, calibration is required. This is challenging due to the large dimension and the outdoor operation, which makes the accurate measurement of the boom position difficult. A camera-based measurement setup is proposed in this work that is tailored for the considered problem. It is shown by measurements that the model is able to achieve a high accuracy with rather small computational costs.
A mathematical model of a direct-fired continuous strip annealing furnace is developed. The first-principle model uses the heat balance to describe the dynamic behavior of the strip and the rolls. ...The mass and the enthalpy balance are employed to calculate the mass, the composition, and the temperature of the flue gas. The heat conduction equation of the furnace wall is discretized by means of the Galerkin method. Furthermore, the convective and radiative heat transfer interconnect all submodels of the furnace. For the calculation of the radiative heat transfer, the zone method is utilized. Finally, the assembled model is reduced by applying the singular perturbation method. A comparison of simulation results with measurement data from a real plant demonstrates the accuracy of the reduced model. Moreover, due to the moderate computational effort, the model is suitable for real-time applications in control and dynamic optimization.
•Tool-force measurements are often deteriorated by the motion and inertia of the tool.•A combined observer strategy is developed to compensate this measurement error.•Part 1 of the observer estimates ...the steady-state actuator behavior by least squares.•Part 2 estimates an unknown disturbance force by a reduced Luenberger observer.
In this paper, a novel two-stage observer strategy for improving the measurement of tool forces is presented. The mass-spring-damper system which inevitably occurs when a tool and a (compliant) force sensor are combined is studied and its adverse influence on the measurement signal is analyzed. The proposed observer consists of two stages. The first stage captures the input-output characteristics from the control input to the tool force by a recursive least-squares estimation algorithm. The estimated tool characteristics are used in a second stage to suppress the oscillations in the measurement signal, which mainly occur due to the mass-spring-damper nature of the tool-sensor combination. In a tailored experimental test rig, which mimics the conditions in magnetic levitation, magnetic bearings, or magnetic strip positioning devices in hot-dip galvanizing lines, the efficacy and the high estimation accuracy of the developed observer strategy are demonstrated.
A nonlinear model predictive controller is designed for a continuous reheating furnace for steel slabs. Based on a first-principles mathematical model, the controller defines local furnace ...temperatures so that the slabs reach their desired final temperatures. The controller is suitable for non-steady-state operating situations and reaching user-defined desired slab temperature profiles. In the control algorithm, a nonlinear unconstrained dynamic optimization problem is solved by the quasi-Newton method. The design of the controller exploits the fact that the considered slab reheating furnace is a continuous production process. Long-term measurement results from an industrial application of the controller demonstrate its reliability and accuracy.
•A model predictive temperature controller is designed for a strip annealing furnace.•The controller is based on a nonlinear first-principles model the furnace.•A dynamic optimization problem with ...equality constraints is solved using the Gauss–Newton method.•The required gradient and the approximated Hessian matrix are analytically determined using an adjoint based method.•The material throughput is systematically optimized.
A nonlinear model predictive controller is designed for the strip temperature in a combined direct- and indirect-fired strip annealing furnace. Based on a tailored first-principles dynamical model and the estimated current system state, the receding horizon controller selects optimal trajectories for both the fuel supply and the strip velocity so that the strip temperature is controlled to its desired target temperature. The controller additionally maximizes the throughput and minimizes the energy consumption. In the control algorithm, the dynamic optimization problem with equality constraints is numerically solved by using the Gauss–Newton method. The gradient and the approximated Hessian matrix of the objective function are analytically computed using an adjoint-based method. The capabilities of the proposed controller are demonstrated for a validated high-fidelity simulation model of an industrial annealing furnace.
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