Harald Aschemann

Sliding-Mode Control of a High-Speed Linear Axis Driven by Pneumatic Muscle Actuators

This paper presents a cascaded sliding-mode (SM) control scheme for a new pneumatic linear axis which could be seen as alternative to an electric direct linear drive. Its guided carriage is driven by a nonlinear mechanism consisting of a rocker with an antagonistic pair of pneumatic muscle actuators arranged at both sides. This innovative drive concept allows for both an increased workspace of approximately 1 m as well as higher carriage velocities of approximately 1.3 m/s as compared to a direct actuation. Modeling of the muscle-driven positioning system leads to a system of four nonlinear differential equations including polynomial approximations of the volume characteristic as well as the force characteristic of the pneumatic muscles. The differential flatness of the system is exploited in combination with SM techniques to stabilize the error dynamics in view of unmodeled dynamics. The internal pressure of each pneumatic muscle is controlled by a fast underlying control loop. Hence, the control design for the outer control loop can be simplified by considering these controlled muscle pressures as ideal control inputs. The control design of the outer control loop involves a decoupling of rocker angle as well as mean internal pressure of both pneumatic muscles as flat outputs. Additionally, model uncertainties in the equation of motion like nonlinear friction are directly counteracted by an observer-based disturbance compensation which reduces the chattering problem. Experimental results show an excellent control performance that outperforms alternative control approaches in a comparison.

Control-oriented modelling of wind turbines using a Takagi-Sugeno model structure

For a horizontal-axis wind turbine (HAWT), a dynamic nonlinear model with four degrees of freedom is derived and transformed into a Takagi-Sugeno (TS) model structure using the sector nonlinearity approach. Thereby, an exact transformation of the nonlinear model is obtained as a weighted combination of linear models. This structure allows for a convenient design of controller and observer structures. The maps of the rotor thrust and torque coefficients can be implemented in the model as look-up tables or, alternatively, as analytical nonlinear functions. Open-loop simulation results of the derived TS model for a reference model turbine are compared to those obtained with the aero-elastic code FAST. The small deviations obtained demonstrate the high model quality of the control-oriented TS model. In future work, the derived TS model shall be used as a basis for the design of fault detection and isolation (FDI) concepts.

Fast Nonlinear MPC for an Overhead Travelling Crane

Abstract This paper presents a nonlinear model predictive control scheme for the two main axes of an overhead travelling crane, which guarantees both tracking of desired trajectories for the crane load and an active damping of crane load oscillations. The main idea of the used NMPC algorithm consists in a minimization of the tracking error at the end of the prediction horizon. That way the computation load can be kept relatively small. The varying length of the rope is considered by gain-scheduling techniques. The position of the crane load is measured by a CMOS camera using the spatial filtering principle. Desired trajectories for the crane load position in the three-dimensional workspace can be tracked independently with high accuracy. Experimental results from an implementation on a test rig show a high control performance.

Comparison of Model-Based Approaches to the Compensation of Hysteresis in the Force Characteristic of Pneumatic Muscles

In this paper, a comparison of three different feedforward compensation strategies that counteract hysteresis effects in the nonlinear force characteristic of pneumatic muscles is presented: The generalized Bouc-Wen model is a dynamic hysteresis model and enables a description of the given highly asymmetric hysteresis, and as alternative hysteresis models for the comparison, the quasi-static Maxwell-slip model and the Prandtl-Ishlinskii model are considered. The parameters of all these hysteresis models have been experimentally identified using evolutionary optimization algorithms. Each of the identified hysteresis models is suitable for an additional feedforward control action in an existing nonlinear control structure for a high-speed linear axis that is actuated by pneumatic muscles to further reduce the tracking error. This cascaded nonlinear control structure consists of fast underlying control loops for the internal muscle pressures and an outer adaptive backstepping control loop for both the carriage position and the mean muscle pressure. Here, the adaptive control part counteracts nonlinear friction and the remaining model uncertainty. Comprehensive experimental results from an implementation of the proposed control approach on a test rig at the Chair of Mechatronics, University of Rostock, Rostock, Germany, point out both the benefits and efficiency of the corresponding feedforward hysteresis compensation strategies.

Anti-sway control for boom cranes

Increasingly boom cranes were used as harbor mobile cranes for container handling. In comparison to gantry cranes or overhead traveling cranes up until now there are only a few automation concepts for boom cranes, due to the dominant nonlinear plant behavior and the problem of measuring the rope angle, which the established methods can not be used. In this paper a trajectory tracking control for boom cranes is presented consisting of decentralized control modules and a trajectory generation module. Nonlinearities are compensated by a feedforward strategy and by gain scheduling adaptation of feedforward and feedback control. The rope angle is reconstructed out of gyroscope measurement signals by disturbance observers. The trajectory tracking control is realized on a harbor mobile crane LIEBHERR LHM 400. Measurement results show the efficiency of the presented control concept.

Passivity-Based Trajectory Control of an Overhead Crane by Interconnection and Damping Assignment

This paper presents a passivity-based control scheme for the two main axes of a 5 t-overhead crane, which guarantees both tracking of desired trajectories for the crane load and an active damping of crane load oscillations. The passivitybased control is performed by interconnection and damping assignment according to the IDA-PBC approach for underactuated systems. The tracking capabilities concerning desired trajectories for the crane load can be significantly improved by introducing feedforward control based on an inverse system model. Furthermore, a reduced-order disturbance observer is utilised for the compensation of nonlinear friction forces. In this paper, feedforward and feedback control as well as observer based disturbance compensation are adapted to the varying system parameters rope length as well as load mass by gain-scheduling techniques. Thereby, desired trajectories for the crane load position in the 3-dimensional workspace can be tracked independently with high accuracy. Experimental results of an implementation on a 5 t-crane show both excellent tracking performance with maximum tracking errors of 2 cm and a high steady-state accuracy.

Interval methods for simulation of dynamical systems with state-dependent switching characteristics

In this paper, an interval arithmetic simulation algorithm is introduced for simulation of continuous-time systems with state-dependent switching between different dynamical models. For that purpose, the conditions for all possible transitions between these models have to be evaluated during simulation to determine the switching times and hence to obtain guaranteed enclosures for all state variables. In contrast to other simulation techniques, all system parameters are defined as interval variables to analyze the effect of uncertainties on the switching times and the dynamical behavior of the complete system

Disturbance estimation and compensation for trajectory control of an overhead crane

This paper presents an observer based control concept for an overhead crane using feedforward and feedback controllers. All control system components have been derived in symbolic form. Therefore, gain scheduling can be utilized to take into account varying system parameters. According to a decentralized control structure, a multibody model is presented for the crane y-axis and the equations of motion are stated. Based on a linearized state space representation, a feedback control law is calculated analytically. The feedforward control design and observer based disturbance rejection are described in detail due to their importance concerning tracking accuracy. The nonlinear friction force acting on the trolley drive and disturbance force acting on the load surface are considered. The effectiveness of the developed control scheme is shown by selected experimental results at a 5t-bridge crane.

Control of a wind turbine with a hydrostatic transmission — An extended linearisation approach

In this paper, a simplified model of the NREL 5MW wind turbine with a hydrostatic transmission is derived. A suitable control scheme is described, and the steady state operating points of the system are calculated. The system is given in extended linearised form, and this form is used to design a gain scheduled linear quadratic regulator (LQR), with wind speed and difference pressure as scheduling parameters. Steady state operating points are used as desired values for feedforward control, and disturbance compensation is implemented to minimise the influence of rotor torque variations. Wind turbines operate in different control modes, with different control objectives which are dependent on wind speed. The developed controller is designed to operate for the entire operational range of the wind turbine. The controller is validated through simulation over a range of wind speeds.

Interval Methods for Control-Oriented Modeling of the Thermal Behavior of High-Temperature Fuel Cell Stacks

Abstract Solid oxide fuel cells (SOFCs) can be used as decentralized energy supply devices for providing electricity and heat directly by converting chemical energy. In such applications of SOFCs, the electric power demand is commonly varying over time. Therefore, all processes in fuel cell systems are typically instationary. For example, the heating and cooling phases for starting up and shutting down the fuel cell system as well as the response to varying electrical load demands characterize the instationarity of the operating conditions for the thermal subprocess. In contrast to most existing control approaches, which only cover stationary operating strategies, our work aims at controlling SOFC systems in instationary operating regions. This means that a mathematical system model for these regions is necessary. Such control-oriented models for the temperature distribution in a fuel cell stack module can be obtained by the method of finite volume discretization. On the basis of the first law of thermodynamics, local energy balances are derived for each volume element, which leads to a system of coupled nonlinear ordinary differential equations. In this paper, parameter identification routines are compared which are based both on classical floating point techniques and on verified interval arithmetic approaches. In particular, interval techniques are employed to deal with imperfect system knowledge expressed by bounded parameter uncertainties and to search for globally instead of locally optimal system parameterizations.