In this paper, a model-based control and state reconstruction of an underground coal gasification (UCG) process is elaborated. In order to deploy model-based control strategies, a sophisticated model of the UCG process based on partial differential equations is approximated with a nonlinear control-oriented model that adequately preserves the fundamental dynamic characteristics of the process. A robust dynamic integral sliding mode control (DISMC) is designed based on the control-oriented model to track the desired heating value, which is one of the key indicators for evaluating the performance of an UCG process. Unknown states required for the model-based control are reconstructed using a gain-scheduled modified Utkin observer (GSMUO). In order to assess the robustness of the nonlinear control and estimation techniques, the water influx phenomenon is considered as an input disturbance. Moreover, the underlying UCG plant model is subjected to parametric variations as well as measurement noise. In order to guarantee the stability of the overall system, the boundedness of the internal dynamics is also proved. To make a fair comparison, the performance of the proposed controller is compared with an integral sliding mode control (ISMC) and a classical proportional-integral (PI) controller. Simulation results highlight the effectiveness of the proposed control scheme in terms of minimum control energy and improved tracking error. Moreover, the simulation study shows that the combination of DISMC and GSMUO exhibit robustness against an input disturbance, parametric uncertainties and measurement noise. (C) 2018 Elsevier Ltd. All rights reserved.

One of the challenging control problems of an underground coal gasification (UCG) process involves maintaining a desired heating value from the extracted product gases. In this paper, a model-based control and state estimation of UCG process is described. For the purpose of control and state estimation, a sophisticated model of the UCG process using partial differential equations is approximated by a gain-scheduled nonlinear control-oriented model. Based on this approximated plant model, a robust integral sliding mode control is designed to track a desired trajectory of the heating value. Furthermore, for the estimation of unknown states of the system, a gain-scheduled modified Utkin observer is designed as well. The robustness of the nonlinear control and estimation techniques is assessed by introducing parametric uncertainties in the UCG plant. The simulation results highlight the effectiveness of the proposed nonlinear control and estimation techniques in comparison to a conventional PI controller.

In this paper, a discrete-time flatness-based control for a twin rotor aerodynamic system with two degrees of freedom is proposed that outperforms a standard quasi-continuous implementation, cf. [1]. A control-oriented state-space model is derived using Lagrange's equations. The resulting nonlinear fourth-order model possesses two control inputs, and is affected by two unknown disturbance torques due to modelling simplifications and unmeasurable torques. Accordingly, a discrete-time Extended Kalman Filter is employed to estimate these lumped disturbances and unmeasurable states as well. The proposed control approach in combination with the discrete-time Extended Kalman Filter is implemented and validated on a laboratory test rig. The effectiveness of the discrete-time flatness-based control is highlighted by experimental results showing an excellent tracking behaviour.

A nonlinear control approach for an innovative engine cooling system in vehicles is presented in this paper. The electrically driven radiator fan is employed as a control input. The engine cooling system represents a special class of nonlinear systems characterized by both matched and mismatched lumped disturbances. Based on a control oriented system representation, a backstepping-based sliding mode control is designed to track desired trajectories of the engine outlet temperature. Moreover, the lumped disturbances are estimated using a gain-scheduled modified Utkin observer. Experiments at a dedicated test-rig depict the effectiveness of the proposed control scheme in comparison to a PI controller.

In this contribution, two robust MIMO backstepping control approaches for a twin rotor aerodynamic system (TRAS) test-rig are considered. The TRAS represents a nonlinear system with significant couplings. A nonlinear multibody model of the TRAS with lumped unknown disturbance torques is derived using Lagrange’s equations. Herewith, both a backstepping-based sliding mode control and an adaptive backstepping control are designed to track desired trajectories for the azimuth angle and the pitch angle. An explicit expression is derived for the reaching time in the case of the backstepping-based sliding mode control. In order to estimate immeasurable angular velocities and unknown disturbance torques for the backstepping-based sliding mode control, a discrete-time extended Kalman filter (EKF) is employed. For the adaptive backstepping, a robust sliding mode differentiator is used instead to estimate the angular velocities. Moreover, in the adaptive backstepping control approach, the disturbance compensation is realised with the help of additional adaptive control parts driven by the tracking errors of the controlled variables. The overall stability of the proposed controllers in combination with the corresponding estimator is investigated thoroughly by simulations. Furthermore, in order to validate the proposed control schemes, experiments are performed on the dedicated test-rig and a comparison of the two proposed control structures is provided as well.

This paper proposes a novel adaptive backstep-ping control for an innovative engine cooling system. The engine cooling system belongs to a special class of nonlinear systems with both matched and mismatched state-dependent lumped disturbances. The parameter update laws resemble a nonlinear reduced-order disturbance observer and guarantee the convergence of the estimated parameter values to the true ones. In each recursive design step, only a single parameter update law is required for each lumped disturbance in contrast to the standard adaptive backstepping control based on overparametrization and tuning functions. An experimental analysis on a dedicated test rig highlights the effectiveness of the proposed novel adaptive backstepping control in terms of asymptotic tracking, global stability and guaranteed parameter convergence.

In this paper, a robust nonlinear control approach based on a simplified control-oriented model of an engine cooling system for vehicles is presented. An electrically driven radiator fan is considered as a control input. Based on the system description, a second-order sliding mode control is proposed to track desired trajectories of the engine outlet temperature. The second-order sliding mode control provides a smooth control action and reduces the chattering phenomenon with the introduction of a first-order time derivative of the sliding manifold. A gain-scheduled modified Utkin sliding mode observer, which uses both an output error feedback and a switching term, is employed to estimate unknown heat flows within the system. The estimated heat flows are used in the control design in order to compensate the disturbances acting on the system. An experimental analysis highlights the effectiveness of the second-order sliding mode control in combination with a sliding mode based observer design.

In this paper, a robust nonlinear control approach based on a control-oriented model of an engine cooling system for vehicles is presented. The angular velocity of an electrically driven radiator fan is considered as the control input to adjust the cooling heat flow corresponding to a desired engine cooling performance. For smooth control actions and an avoidance of chattering, a dynamic sliding mode control is presented to track the desired trajectories of the engine outlet temperature. For the estimation of unmeasured heat flows, a gain-scheduled version of a modified Utkin sliding mode observer is employed, which uses both an output error feedback and a switching term for the stabilisation of the observer error. The estimated heat flows are used in the control design to compensate for the disturbances acting on the system. Experiments on a dedicated test rig highlight the effectiveness of the robust observer-based control strategy during the normal vehicle operation as well as a start/stop scenario.

In this paper, a passivity-based tracking control for a twin rotor aerodynamic system (TRAS) with two degrees of freedom is proposed. A control-oriented state-space model is derived using Lagrange's method. The resulting nonlinear fourth-order model possesses two control inputs, and is affected by two unknown disturbance torques due to modelling simplifications and unmeasurable torques. Accordingly, an Unscented Kalman Filter (UKF) is employed to estimate these lumped disturbances and unmeasurable states as well. The proposed passivity-based control in combination with UKF is implemented and validated on a laboratory test rig. The effectiveness of the passivity-based control is highlighted by experimental results showing an excellent tracking behaviour.

In this paper, a robust nonlinear control of an engine cooling system for vehicles is presented, where an electrically driven radiator fan serves as the control input. A simplified control-oriented model of the engine cooling system is derived using the first law of thermodynamics. The control design is based on an integral sliding mode approach and aims at tracking of desired trajectories for the engine outlet temperature. A gain-scheduled modified Utkin sliding mode observer, which uses both a switching term and an output error feedback, is employed to estimate unknown heat ows acting as system disturbances. The estimated heat ows are used in the control structure for a disturbance compensation. An experimental analysis highlights the effectiveness of the integral sliding mode control strategy in combination with the gain-scheduled sliding mode observer.

In this paper, a decentralised tracking control based on extended linearisation techniques is presented for a two rotor laboratory helicopter with two degrees of freedom. Employing Lagrange's equations, a nonlinear control-oriented state-space model can be derived. It is rewritten in a quasi-linear form – without any simplifications – with state-dependent matrices as a basis for the decentralised feedforward and feedback control design. The control task consists in tracking accurately desired trajectories for both the azimuth angle and the pitch angle. Due to unmeasurable states as well as uncertainties stemming from both model simplifications at modelling and unknown disturbance torques, an unscented Kalman filter is employed and combined with a discrete-time implementation of the nonlinear control law. The eficiency of the proposed controller is demonstrated by results from an experimental set-up.

In this paper, a multi-variable nonlinear control-oriented model of a twin rotor aerodynamic system (TRAS) is presented. The mathematical description of the multibody system is derived using Lagrange's equations. Based on the resulting state-space representation, a multi-variable integral sliding mode control is designed to accurately track desired trajectories for both the azimuth angle and the pitch angle. Due to unmeasurable states and uncertainties stemming from simplifications at modelling as well as disturbance torques, a discrete-time extended Kalman filter (EKF) is employed and combined with a discrete-time implementation of the nonlinear control law. The proposed control strategy allows for an excellent tracking behaviour as highlighted by experimental results.

In this paper, a nonlinear control approach of an innovative engine cooling system for vehicles is presented. The electrically driven coolant pump and a servo-controlled bypass valve as control inputs, however, are subject to saturation due to physical limitations of the maximum pump volume flow and the limited opening section of the bypass valve. Based on a control-oriented system representation, a robust decentralized control employing sliding-mode techniques is proposed: an input-output linearizing control is designed for the engine outlet temperature, whereas an exact linearization is performed for the engine inlet temperature. At this control design, the given actuator limitations are explicitly taken into account. The controllers are implemented with small sampling time and combined with a discrete-time Extended Kalman Filter that estimates unknown heat flows within the system. In an experimental investigation, the performance of two alternative stabilizing control laws is compared: a linear stabilizing control law as reference and the robust sliding-mode approach leading to a nonlinear error dynamics. The obtained results highlight the effectiveness and the control performance of the proposed robust control strategy.

In this paper, a multi-variable nonlinear control of a twin rotor aerodynamical system (TRAS) is presented. A control-oriented state-space model with four states is derived employing Lagrange's equations. Using this system representation, a multi-variable flatness-based control is designed for an accurate trajectory tracking concerning both the pitch angle characterising the vertical motion and the azimuth angle related to the horizontal motion. Due to unmeasurable states as well as disturbance torques affecting the pitch axis and the azimuth axis, a discrete-time Extended Kalman Filter (EKF) is employed and combined with a discrete-time implementation of the multi-variable flatness-based control. The effectiveness of the proposed control strategy is highlighted by experimental results from a test rig that show an excellent tracking behaviour.

A cascaded control strategy for an innovative Duocopter test stand - a helicopter with two rotors combined with a guiding mechanism - is presented in this paper. The guiding mechanism consists of a rocker arm with a sliding carriage that enforces a planar workspace of the Duocopter. The Duocopter is connected to the carriage by a rotary joint and offers 3 degrees of freedom. The derived system model has similarities with a PVTOL and a planar model of a quadrocopter but involves additional terms due to the guiding mechanism. In the paper, a model-based cascaded control strategy is proposed: the outer MIMO control loop is given by the inverted system model to control the horizontal and the vertical Duocopter position with a nonlinear error dynamics derived from backstepping techniques. The rotation angle of the Duocopter is controlled in a linear inner control loop of high bandwidth. Due to uncertain system parameters and reasonable simplifications at the modelling of the test stand, the control structure is extended by an unscented Kalman filter. Thereby, an excellent tracking performance in vertical and horizontal direction can be achieved. The efficiency of the proposed control strategy is demonstrated by both simulations and experiments.

In this paper, a nonlinear control-oriented model of the thermal behaviour of an engine cooling system for vehicles is presented. The volume flow of an electrically driven coolant pump and the angular velocity of a radiator-fan unit serve as control inputs in a flatness-based nonlinear control approach. A constrained control problem arises due to the given physical bounds on the actuator inputs. Based on the derived system representation, a flatness-based control is designed that allows for tracking of desired trajectories for the engine outlet temperature as well as the radiator outlet temperature. The control structure is implemented in a time-discretised form. Furthermore, a discrete-time Extended Kalman Filter (EKF) is employed which estimates unmeasurable heat flows affecting the system. An experimental analysis using both feasible trajectories and infeasible trajectories, leading to actuator saturation, highlights the effectiveness of the model-based control approach.

A nonlinear control approach of an innovative engine cooling system for vehicles is presented in this paper. The electrically driven coolant pump and a servo-controlled bypass valve as control inputs, however, are subject to saturation due to physical limitations of the maximum pump volume flow and the limited opening section of the bypass valve. Based on a control-oriented system representation, a decoupling, input-output-linearising control is designed for the engine outlet temperature and the engine inlet temperature. At this control design, the given actuator limitations are explicitly taken into account. The multi-variable control is implemented with a small sampling time and combined with a discrete-time Extended Kalman Filter that estimates unknown heat flows within the system. Experimental results from a dedicated test rig highlight the effectiveness and the performance of the proposed control approach.

In this paper, a nonlinear control approach based on a control-oriented model of an engine cooling system for vehicles is presented. An electrically driven coolant pump and a servo-controlled bypass valve act as control inputs. Due to physical limitations regarding the volume flow provided by the coolant pump as well as the opening section of the servo-controlled bypass valve, a constrained control problem arises. Therefore, a nonlinear model-predictive controller is employed, which explicitly takes the actuator limitations into account. A reduced-order disturbance observer is used to estimate unmeasured heat flows within the system in order to obtain a reliable prediction. An experimental analysis highlights the effectiveness of the nonlinear model-predictive control strategy in combination with a reduced-order observer.

The focus of this paper is to develop reliable observer and filtering techniques for finite-dimensional battery models that adequately describe the charging and discharging behaviors. For this purpose, an experimentally validated battery model taken from the literature is extended by a mathematical description that represents parameter variations caused by aging. The corresponding disturbance models account for the fact that neither the state of charge, nor the above-mentioned parameter variations are directly accessible by measurements. Moreover, this work provides a comparison of the performance of different observer and filtering techniques as well as a development of estimation procedures that guarantee a reliable detection of large parameter variations. For that reason, different charging and discharging current profiles of batteries are investigated by numerical simulations. The estimation procedures considered in this paper are, firstly, a nonlinear Luenberger-type state observer with an offline calculated gain scheduling approach, secondly, a continuous-time extended Kalman filter and, thirdly, a hybrid extended Kalman filter, where the corresponding filter gains are computed online.