| 1. |
|
|
| 2. |
|
|
| 3. |
- Christiansson, Anna-Karin, 1947-, et al.
(author)
-
Low order sampled-data H∞ control
- 2003
-
In: Decision and Control, 2003. Proceedings. 42nd IEEE Conference on. ; 3, s. 2308 - 2313
-
Conference paper (peer-reviewed)abstract
- A method for obtaining low order sampled-data H∞ controllers is presented. The method is mainly based on a parametric static feedback controller for a plant that is augmented with the controller dynamics. The design of a full-order controller is a convex problem, while the optimisation problem for lower order controllers is non convex. The proposed method starts with design of a full-order sampled-data controller using Riccati equations. Then this controller is reduced by an ordinary model reduction technique, and the reduced controller is used as an initial value for an iterative procedure using linear matrix inequalities (LMIs) in the search for an optimal controller. The matrix inequalities are in fact linear in either the Lyapunov matrix or the static controller matrix, why the solution to the non convex problem fundamentally is given by a bilinear matrix inequality (BMI). The order of the controller is reduced until the closed loop performance degrades too much. Simulations are shown for the control of a time delayed SISO-plant where the controller order can be reduced from 8th to 3rd order. Results are also shown from control of a MIMO-model of a jet engine where the reduction is successful from 15th to 4th order. It is argued that the non convexity is handled efficiently since the procedure uses a model reduction of the full-order controller as initial value.
|
|
| 4. |
- Christiansson, Anna-Karin, 1947-, et al.
(author)
-
Mixed continuous/discrete-time output feedback H∞ control : A unified approach
- 1999
-
In: European Control Conference, ECC 1999 - Conference Proceedings. - 9783952417355 ; , s. 4077-4082
-
Conference paper (peer-reviewed)abstract
- A Riccati equation (RE) based solution to the H∞ optimal control problem for mixed continuous/discrete-time systems is presented. The results unify a number of recently penetrated H∞ control problems. In the infinite-horizon case a periodic behaviour is assumed, and it is shown how the related continuous RE with jumps can be replaced by an equivalent discrete periodic RE. A related algebraic RE, which involves the system behaviour during one period, then can be formulated and solved by standard methods. Typical applications are control of continuous-time or discrete-time periodic systems, as well as multirate and sampled-data control, including mixed continuous and sampled-data measurements. © 1999 EUCA.
|
|
| 5. |
- Christiansson, Anna-Karin, 1947, et al.
(author)
-
Sampled-Data H-infinity-Control for Time-Varying Hybrid Systems
- 2001
-
In: Dynamics of Continuous, Discrete and Impulsive Systems Series B: Applications and Algorithms. - 1492-8760. ; 8:4, s. 427-444
-
Journal article (peer-reviewed)abstract
- This paper presents sampled-data H-infinity-control of linear mixed continuous-time and discrete-time systems, including a mix of continuous-time and discrete-time performance signals and disturbances. However, neither continuous-time control signals nor continuous-time measurements are included. The sampling may well be multirate, i.e. different signals may be sampled by different rates, as long as a periodic pattern is repeated over the period, consisting of a number of sampling steps. In fact, the results are applicable even to arbitrary linear time-varying systems.The sampled-data system is discretised such that the continuous-time performance is reflected in the discretised or "lifted" system. This lifted system is combined with discrete-time updates at the sampling instants to achieve the sampled-data controller. The "hold-states" case is presented as a special application, when there is also a hold circuit at the controller output. The continuous-time Riccati equations with discrete-time updates then can be replaced by one discrete-time static feedback and filter Riccati equation respectively, which also reflect the intersample behaviour.Furthermore, convergence results between the discretised Riccati solutions and the corresponding continuous-time solutions are shown, when the sampling interval decreases towards zero, Simulations are shown when the results are applied to the control of a MIMO jet-engine model.
|
|
| 6. |
|
|
| 7. |
|
|
| 8. |
|
|
| 9. |
- Hagqvist, Petter, 1986, et al.
(author)
-
Emissivity compensated spectral pyrometry-algorithm and sensitivity analysis
- 2014
-
In: Measurement Science and Technology. - : IOP Publishing. - 0957-0233 .- 1361-6501. ; 25:2
-
Journal article (peer-reviewed)abstract
- In order to solve the problem of non-contact temperature measurements on an object with varying emissivity, a new method is herein described and evaluated. The method uses spectral radiance measurements and converts them to temperature readings. It proves to be resilient towards changes in spectral emissivity and tolerates noisy spectral measurements. It is based on an assumption of smooth changes in emissivity and uses historical values of spectral emissivity and temperature for estimating current spectral emissivity. The algorithm, its constituent steps and accompanying parameters are described and discussed. A thorough sensitivity analysis of the method is carried out through simulations. No rigorous instrument calibration is needed for the presented method and it is therefore industrially tractable.
|
|
| 10. |
- Hagqvist, Petter, et al.
(author)
-
Resistance based iterative learning control of additive manufacturing with wire
- 2015
-
In: Mechatronics (Oxford). - : Elsevier BV. - 0957-4158 .- 1873-4006. ; 31, s. 116-123
-
Journal article (peer-reviewed)abstract
- This paper presents successful feed forward control of additive manufacturing of fully dense metallic components. The study is a refinement of former control solutions of the process, providing more robust and industrially acceptable measurement techniques. The system uses a solid state laser that melts metal wire, which in turn is deposited and solidified to build the desired solid feature on a substrate. The process is inherently subjected to disturbances that might hinder consecutive layers to be deposited appropriately. The control action is a modified wire feed rate depending on the surface of the deposited former layer, in this case measured as a resistance. The resistance of the wire stick-out and the weld pool has shown to give an accurate measure of the process stability, and a solution is proposed on how to measure it. By controlling the wire feed rate based on the resistance measure, the next layer surface can be made more even. A second order iterative learning control algorithm is used for determining the wire feed rate, and the solution is implemented and validated in an industrial setting for building a single bead wall in titanium alloy. A comparison is made between a controlled and an uncontrolled situation when a relevant disturbance is introduced throughout all layers. The controller proves to successfully mitigate these disturbances and maintain stable deposition while the uncontrolled deposition fails.
|
|
