| 1. |
- Härkegård, Ola, 1947-, et al.
(author)
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Flight Control Design using Backstepping
- 2000
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Reports (other academic/artistic)abstract
- Today the prevailing nonlinear design method for aircraft flight control is feedback linearization. This paper presents a new method to deal with the nonlinear aerodynamic forces and moments acting on the aircraft: backstepping. Specifically, we derive backstepping control laws for angle of attack and sideslip control that requireless knowledge of the lift and side forces compared to feedback linearization designs. The control laws are made adaptive to errors in the aerodynamic moment coefficients using nonlinear observer techniques.
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| 2. |
- Andersson, Magnus, et al.
(author)
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A Simulation and Animation Tool for Studying Multivariable Control
- 2002
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In: Proceedings of the 15th IFAC World Congress. - 9783902661746 ; , s. 1432-1432
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Conference paper (peer-reviewed)abstract
- A simulation and animation tool for education in multivariable control is presented. The purpose of the tool is to support studies of various aspects of multivariable dynamical systems and design of multivariable feedback control systems. Different ways to use this kind of tool in control education are also presented and discussed.
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| 3. |
- Bergman, Kristoffer, 1990-, et al.
(author)
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An Optimization-Based Receding Horizon Trajectory Planning Algorithm
- 2020
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In: IFAC-PapersOnLine. - : ELSEVIER. - 2405-8963. ; , s. 15550-15557
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Conference paper (peer-reviewed)abstract
- This paper presents an optimization-based receding horizon trajectory planning algorithm for dynamical systems operating in unstructured and cluttered environments. The proposed approach is a two-step procedure that uses a motion planning algorithm in a first step to efficiently find a feasible, but possibly suboptimal, nominal solution to the trajectory planning problem where in particular the combinatorial aspects of the problem are solved. The resulting nominal trajectory is then improved in a second optimization-based receding horizon planning step which performs local trajectory refinement over a sliding time window. In the second step, the nominal trajectory is used in a novel way to both represent a terminal manifold and obtain an upper bound on the cost-to-go online. This enables the possibility to provide theoretical guarantees in terms of recursive feasibility, objective function value, and convergence to the desired terminal state. The established theoretical guarantees and the performance of the proposed algorithm are verified in a set of challenging trajectory planning scenarios for a truck and trailer system.
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| 4. |
- Bergman, Kristoffer, 1990-
(author)
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Exploiting Direct Optimal Control for Motion Planning in Unstructured Environments
- 2021
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Doctoral thesis (other academic/artistic)abstract
- During the last decades, motion planning for autonomous systems has become an important area of research. The high interest is not the least due to the development of systems such as self-driving cars, unmanned aerial vehicles and robotic manipulators. The objective in optimal motion planning problems is to find feasible motion plans that also optimize a performance measure. From a control perspective, the problem is an instance of an optimal control problem. This thesis addresses optimal motion planning problems for complex dynamical systems that operate in unstructured environments, where no prior reference such as road-lane information is available. Some example scenarios are autonomous docking of vessels in harbors and autonomous parking of self-driving tractor-trailer vehicles at loading sites. The focus is to develop optimal motion planning algorithms that can reliably be applied to these types of problems. This is achieved by combining recent ideas from automatic control, numerical optimization and robotics.The first contribution is a systematic approach for computing local solutions to motion planning problems in challenging unstructured environments. The solutions are computed by combining homotopy methods and direct optimal control techniques. The general principle is to define a homotopy that transforms, or preferably relaxes, the original problem to an easily solved problem. The approach is demonstrated in motion planning problems in 2D and 3D environments, where the presented method outperforms a state-of-the-art asymptotically optimal motion planner based on random sampling.The second contribution is an optimization-based framework for automatic generation of motion primitives for lattice-based motion planners. Given a family of systems, the user only needs to specify which principle types of motions that are relevant for the considered system family. Based on the selected principle motions and a selected system instance, the framework computes a library of motion primitives by simultaneously optimizing the motions and the terminal states.The final contribution of this thesis is a motion planning framework that combines the strengths of sampling-based planners with direct optimal control in a novel way. The sampling-based planner is applied to the problem in a first step using a discretized search space, where the system dynamics and objective function are chosen to coincide with those used in a second step based on optimal control. This combination ensures that the sampling-based motion planner provides a feasible motion plan which is highly suitable as warm-start to the optimal control step. Furthermore, the second step is modified such that it also can be applied in a receding-horizon fashion, where the proposed combination of methods is used to provide theoretical guarantees in terms of recursive feasibility, worst-case objective function value and convergence to the terminal state. The proposed motion planning framework is successfully applied to several problems in challenging unstructured environments for tractor-trailer vehicles. The framework is also applied and tailored for maritime navigation for vessels in archipelagos and harbors, where it is able to compute energy-efficient trajectories which complies with the international regulations for preventing collisions at sea.
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| 5. |
- Bergman, Kristoffer, 1990-
(author)
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On Motion Planning Using Numerical Optimal Control
- 2019
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Licentiate thesis (other academic/artistic)abstract
- During the last decades, motion planning for autonomous systems has become an important area of research. The high interest is not the least due to the development of systems such as self-driving cars, unmanned aerial vehicles and robotic manipulators. In this thesis, the objective is not only to find feasible solutions to a motion planning problem, but solutions that also optimize some kind of performance measure. From a control perspective, the resulting problem is an instance of an optimal control problem. In this thesis, the focus is to further develop optimal control algorithms such that they be can used to obtain improved solutions to motion planning problems. This is achieved by combining ideas from automatic control, numerical optimization and robotics.First, a systematic approach for computing local solutions to motion planning problems in challenging environments is presented. The solutions are computed by combining homotopy methods and numerical optimal control techniques. The general principle is to define a homotopy that transforms, or preferably relaxes, the original problem to an easily solved problem. The approach is demonstrated in motion planning problems in 2D and 3D environments, where the presented method outperforms both a state-of-the-art numerical optimal control method based on standard initialization strategies and a state-of-the-art optimizing sampling-based planner based on random sampling.Second, a framework for automatically generating motion primitives for lattice-based motion planners is proposed. Given a family of systems, the user only needs to specify which principle types of motions that are relevant for the considered system family. Based on the selected principle motions and a selected system instance, the algorithm not only automatically optimizes the motions connecting pre-defined boundary conditions, but also simultaneously optimizes the terminal state constraints as well. In addition to handling static a priori known system parameters such as platform dimensions, the framework also allows for fast automatic re-optimization of motion primitives if the system parameters change while the system is in use. Furthermore, the proposed framework is extended to also allow for an optimization of discretization parameters, that are are used by the lattice-based motion planner to define a state-space discretization. This enables an optimized selection of these parameters for a specific system instance.Finally, a unified optimization-based path planning approach to efficiently compute locally optimal solutions to advanced path planning problems is presented. The main idea is to combine the strengths of sampling-based path planners and numerical optimal control. The lattice-based path planner is applied to the problem in a first step using a discretized search space, where system dynamics and objective function are chosen to coincide with those used in a second numerical optimal control step. This novel tight combination of a sampling-based path planner and numerical optimal control makes, in a structured way, benefit of the former method’s ability to solve combinatorial parts of the problem and the latter method’s ability to obtain locally optimal solutions not constrained to a discretized search space. The proposed approach is shown in several practically relevant path planning problems to provide improvements in terms of computation time, numerical reliability, and objective function value.
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| 6. |
- Brannmark, Cecilia, et al.
(author)
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Mass and Information Feedbacks through Receptor Endocytosis Govern Insulin Signaling as Revealed Using a Parameter-free Modeling Framework
- 2010
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In: Journal of Biological Chemistry. - : American Society for Biochemistry and Molecular Biology. - 0021-9258 .- 1083-351X. ; 285:26, s. 20171-20179
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Journal article (peer-reviewed)abstract
- Insulin and other hormones control target cells through a network of signal-mediating molecules. Such networks are extremely complex due to multiple feedback loops in combination with redundancy, shared signal mediators, and cross-talk between signal pathways. We present a novel framework that integrates experimental work and mathematical modeling to quantitatively characterize the role and relation between coexisting submechanisms in complex signaling networks. The approach is independent of knowing or uniquely estimating model parameters because it only relies on (i) rejections and (ii) core predictions (uniquely identified properties in unidentifiable models). The power of our approach is demonstrated through numerous iterations between experiments, model-based data analyses, and theoretical predictions to characterize the relative role of co-existing feedbacks governing insulin signaling. We examined phosphorylation of the insulin receptor and insulin receptor substrate-1 and endocytosis of the receptor in response to various different experimental perturbations in primary human adipocytes. The analysis revealed that receptor endocytosis is necessary for two identified feedback mechanisms involving mass and information transfer, respectively. Experimental findings indicate that interfering with the feedback may substantially increase overall signaling strength, suggesting novel therapeutic targets for insulin resistance and type 2 diabetes. Because the central observations are present in other signaling networks, our results may indicate a general mechanism in hormonal control.
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| 7. |
- Chen, Ke Wang, et al.
(author)
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Estimation of the Primary Current in a Saturated Transformer
- 1991
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In: Proceedings of the 30th IEEE Conference on Decision and Control. - Linköping : Linköping University. - 0780304500 ; , s. 2363-2365 vol.3
-
Conference paper (peer-reviewed)abstract
- It is pointed out that, when a current in a power system is measured using a transformer, the measurement can be distorted by transformer saturation. The authors examine two methods of estimating the primary current from the secondary in the presence of saturation. The first is based on an extended Kalman filter, while the second is based on an off-line Gauss-Newton method
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| 8. |
- Edström, Krister, et al.
(author)
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Algorithmic, Physically based Mode Initialization when Simulating Hybrid Systems
- 2002
-
In: Proceedings of the Institution of mechanical engineers. Part I, journal of systems and control engineering. - : SAGE Publications. - 0959-6518 .- 2041-3041. ; 216:I1, s. 65-72
-
Journal article (peer-reviewed)abstract
- In the simulation of hybrid systems, discontinuities can appear at mode changes. An algorithm is presented that gives initial values for the continuous state variables in a new mode. The algorithm is based on a switched bond graph representation of the system, and it handles discontinuities introduced by a changed number of state variables at a mode change. The algorithm is obtained by integrating the bond graph relations over the mode change and assuming that the physical variables are bounded. This gives a relation between the variables before and after the mode change. It is proved here that the equations for the new initial conditions are solvable. The algorithm is related to a singular perturbation theory by replacing the discontinuity by a fast continuous change. The action is considered of a single switch and the corresponding continuous change, tuned by a single parameter. By letting this parameter tend to zero, the same initial state values are achieved as those derived by the presented algorithm. The algorithm is also related to physical principles such as charge conservation.
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| 9. |
- Fliess, M, et al.
(author)
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An Algebraic Approach to Linear and Nonlinear Control
- 1993
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In: Essays on Control. - Boston ; Basel : Birkhäuser. - 0817636706 - 3764336706 ; , s. 223--267
-
Book chapter (peer-reviewed)abstract
- The analysis and design of control systems has been greatly influenced by the mathematical tools being used. Maxwell introduced linear differential equations in the 1860’s. Nyquist, Bode and others started the systematic use of tranfer functions, utilizing complex analysis in the 1930’s. Kalman brought forward state space analysis around 1960. For nonlinear systems, differential geometric concepts have been of great value recently. We will argue here that algebraic methods can be very useful for both linear and nonlinear systems. To give some motivation we will begin by looking at a few examples.
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| 10. |
- Fliess, Michel, et al.
(author)
-
An Algebraic Approach to Linear and Nonlinear Control
- 1994
-
Reports (other academic/artistic)abstract
- The analysis and design of control systems has been greatly influenced by the mathematical tools being used. Maxwell introduced linear differential equations in the 1860’s. Nyquist, Bode and others started the systematic use of tranfer functions, utilizing complex analysis in the 1930’s. Kalman brought forward state space analysis around 1960. For nonlinear systems, differential geometric concepts have been of great value recently. We will argue here that algebraic methods can be very useful for both linear and nonlinear systems. To give some motivation we will begin by looking at a few examples.
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