Ag Bram de Jager

Survey A review of methods for input/output selection

Control system design involves input/output (IO) selection, that is, decisions on the number, the place, and the type of actuators and sensors. The choice of inputs and outputs affects the performance, complexity, and costs of the control system. Due to the combinatorial nature of the selection problem, systematic methods are needed to complement ones intuition, experience, and physical insight. This paper reviews the currently known IO selection methods, which aids the control engineer in picking a suitable method for the problem at hand. The methods are grouped according to the control system property that is addressed and applications are grouped according to the considered control systems. A set of criteria is proposed that a good IO selection method should possess. It is used to assess and compare the methods and it could be used as a guideline for new methods. The state of the art in IO selection is sketched and directions for further research are mentioned.

Is Closed-Loop SCR Control Required to Meet Future Emission Targets?

To meet 2010 emission targets, optimal SCR system performance is required. In addition, attention has to be paid to in-use compliance requirements. Closed-loop control seems an attractive option to meet the formulated goals. This study deals with the potential and limitations of closed-loop SCR control. High NO x conversion in combination with acceptable NH 3 slip can be realized with an open-loop control strategy. However, closed-loop control is needed to make the SCR system robust for urea dosage inaccuracy, catalyst ageing and NO x engine-out variations. Then, the system meets conformity of production and in-use compliance norms. To demonstrate the potential of closed-loop SCR control, a NO x sensor based control strategy with crosssensitivity compensation is compared with an adaptive surface coverage/NH 3 slip control strategy and an openloop strategy. The adaptive surface coverage/NH 3 slip control strategy shows best performance over simulated ESC and ETC cycles. SCR catalyst dynamics, time delay in the urea injection and maximum NH 3 slip targets limit the performance of closed-loop SCR control. If new reagent dosage systems and future catalyst technology are able to relieve these limitations, closed-loop control has the potential to reduce the calibration effort and to improve the transient control performance.

Modeling and identification for high-performance robot control: an RRR-robotic arm case study

This paper explains a procedure for getting models of robot kinematics and dynamics that are appropriate for robot control design. The procedure consists of the following steps: 1) derivation of robot kinematic and dynamic models and establishing correctness of their structures; 2) experimental estimation of the model parameters; 3) model validation; and 4) identification of the remaining robot dynamics, not covered with the derived model. We give particular attention to the design of identification experiments and to online reconstruction of state coordinates, as these strongly influence the quality of the estimation process. The importance of correct friction modeling and the estimation of friction parameters are illuminated. The models of robot kinematics and dynamics can be used in model-based nonlinear control. The remaining dynamics cannot be ignored if high-performance robot operation with adequate robustness is required. The complete procedure is demonstrated for a direct-drive robotic arm with three rotational joints.

Direct data-driven recursive controller unfalsification with analytic update

Unfalsified control is a data-driven, plant-model-free controller design method, which recursively falsifies controllers that fail to meet the specified performance requirement. In ellipsoidal unfalsified control, the region of controllers that are unfalsified, the unfalsified set, is described by an ellipsoid. Due to the combination of the performance requirement and controller structure, the approximate update of the unfalsified set can be computed analytically, resulting in a computationally cheap algorithm. Conditions for stability of ellipsoidal unfalsified control are presented, and the effectiveness of the proposed algorithm is shown in a simulation.

Velocity trajectory optimization in Hybrid Electric trucks

Hybrid Electric Vehicles (HEVs) enable fuel savings by re-using kinetic and potential energy that was recovered and stored in a battery during braking or driving down hill. Besides, the vehicle itself can be seen as a storage device, where kinetic energy can be stored and retrieved by changing the forward velocity. It is beneficial for fuel consumption to optimize the velocity trajectory in two ways; i) to assist the driver in tracking an optimal velocity trajectory (e.g. input to an Adaptive Cruise Controller); ii) to estimate the future power request trajectory which can be used to optimize the hybrid components use. Taking advantage of satellite navigation, together with the vehicles current mass and road load parameters, an optimization problem is formulated, and solved for a driver defined time constraint. Despite tight velocity constraints, this can result in 5% fuel saving compared to a Cruise Controller with constant velocity setpoint. The benefit of velocity trajectory optimization is indicated with experimental results.

Brief Positive feedback stabilization of centrifugal compressor surge

Stable operation of axial and centrifugal compressors is limited towards low mass flows due to the occurrence of surge. The stable operating region can be enlarged by active control. In this study, we use a control valve which is fully closed in the desired operating point and only opens to stabilize the system around this point. As a result, only nonnegative control values are allowed, which complicates the controller design considerably. A novel positive feedback controller is proposed which is based on the pole placement technique. This controller has been successfully applied to a laboratory-scale gas turbine installation. Initial experiments show that the surge point mass flow can be reduced by at least 7%. Using this efficient control strategy, stable operation in the desired operating point is maintained with small average control valve mass flow.

Solution for state constrained optimal control problems applied to power split control for hybrid vehicles

This paper presents a numerical solution for scalar state constrained optimal control problems. The algorithm rewrites the constrained optimal control problem as a sequence of unconstrained optimal control problems which can be solved recursively as a two point boundary value problem. The solution is obtained without quantization of the state and control space. The approach is applied to the power split control for hybrid vehicles for a predefined power and velocity trajectory and is compared with a Dynamic Programming solution. The computational time is at least one order of magnitude less than that for the Dynamic Programming algorithm for a superior accuracy.

Data-driven multivariable controller design using Ellipsoidal Unfalsified Control

Ellipsoidal unfalsified control is a data-driven, plant-model-free control design method. In this work, this framework is extended to cover full-block multivariable controllers. A new controller structure and a sequential update procedure are proposed. A simulation example shows the effectiveness of the method.

Control-oriented modelling of occupants in frontal impacts

This paper presents manageable, mathematical models of a vehicle occupant and a belt restraint system. These low-order models are relevant in the development of controlled restraint systems, which aim at lowering injury criteria by real-time control of the occupant motion. The models can be employed for control design and real-time injury prediction, the main components of controlled restraint systems. Several low-order models are constructed with first principles of physics and through knowledge obtained from a sensitivity analysis of validated, complex occupant models. The biomechanical responses of the low-order models, related to neck and thoracic injury criteria are validated with the results of the complex models. They are found to be valid for 5th, 50th and 95th percentile Hybrid III dummies in a range of frontal impact scenarios. The conclusion of this study is that thoracic and neck injury criteria in frontal impact can be accurately assessed with relatively simple occupant models, which are required for real-time control of injury-related biomechanical responses.

Actuator and sensor selection for an active vehicle suspension aimed at robust performance

A recently presented method for actuator and sensor selection for linear control systems is applied and evaluated for an active vehicle suspension control problem. The aim is to eliminate the actuator/sensor combinations for which no controller exists that achieves a specified level of robust performance. Complete controller synthesis is avoided by using necessary conditions for robust performance. Due to this, it cannot be guaranteed that a stabilizing and robustly performing controller exists for the combinations satisfying the conditions. This is a major shortcoming of the method. Depending on the application and implementation, the computation time consumed by the selection procedure can be large.