| 1. |
- Barbosa, Filipe Marques, et al.
(författare)
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Fast or Cheap: Time and Energy Optimal Control of Ship-to-Shore Cranes
- 2023
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Ingår i: Special issue: 22nd IFAC World Congress. - : ELSEVIER. ; , s. 3126-3131
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Konferensbidrag (refereegranskat)abstract
- This paper addresses the trade-off between time and energy-efficiency for the problem of loading and unloading a ship. Container height constraints and energy consumption and regeneration are dealt with. We build upon a previous work that introduced a coordinate system suitable to deal with container avoidance constraints and incorporate the energy related modeling. In addition to changing the coordinate system, standard epigraph reformulations result in an optimal control problem with improved numerical properties. The trade-of is dealt with through the use of weighting of the total time and energy consumption in the cost function. An illustrative example is provided, demonstrating that the energy consumption can be substantially reduced while retaining approximately the same loading time.
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| 2. |
- Barbosa, Filipe Marques, et al.
(författare)
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Time-optimal control of cranes subject to container height constraints
- 2022
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Ingår i: Proceedings of 2022 American Control Conference (ACC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665451963 - 9781665451970 - 9781665494809 ; , s. 3558-3563
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The productivity and efficiency of port operations strongly depend on how fast a ship can be unloaded and loaded again. With this in mind, ship-to-shore cranes perform the critical task of transporting containers into and onto a ship and must do so as fast as possible. Though the problem of minimizing the time spent in moving the payload has been addressed in previous studies, the different heights of the container stacks have not been the focus. In this paper, we perform a change of variable and reformulate the optimization problem to deal with the constraints on the stack heights. As consequence, these constraints become trivial and easy to represent since they turn into bound constraints when the problem is discretized for the numerical solver. To validate the idea, we simulate a small-scale scenario where different stack heights are used. The results confirm our idea and the representation of the stack constraints become indeed trivial. This approach is promising to be applied in real crane operations and has the potential to enhance their automation.
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| 3. |
- Dhar, Abhishek, et al.
(författare)
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Disturbance-Parametrized Robust Lattice-based Motion Planning
- 2023
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Ingår i: IEEE Transactions on Intelligent Vehicles. - 2379-8858 .- 2379-8904.
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Tidskriftsartikel (refereegranskat)abstract
- This paper introduces a disturbance-parametrized (DP) robust lattice-based motion-planning framework for nonlinear systems affected by bounded disturbances. A key idea in this work is to rigorously exploit the available knowledge about the disturbance, starting already offline at the time when a library of DP motion primitives is computed and ending not before the motion has been executed online. Given an up-to-date-estimate of the disturbance, the lattice-based motion planner performs a graph search online, to non-conservatively compute a disturbance aware optimal motion plan with formally motivated margins to obstacles. This is done utilizing the DP motion primitives, around which tubes are generated utilizing a suitably designed robust controller. The sizes of the tubes are dependent on the upper bounds of the disturbance appearing in the error between the actual system trajectory and the DP nominal trajectory, which in turn along with the overall optimality of the plan is dependant on the user-selected resolution of the available disturbance estimates. Increasing the resolution of the disturbance parameter results in smaller sizes of tubes around the motion primitives and can significantly reduce the conservativeness compared to traditional approaches, thus increasing the performance of the computed motion plans. The proposed strategy is implemented on an Euler-Lagrange-based ship model which is affected by a significant wind disturbance and the efficiency of the strategy is validated through a suitable simulation example.
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| 4. |
- Forsling, Robin, 1988-, et al.
(författare)
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Conservative Linear Unbiased Estimation Under Partially Known Covariances
- 2022
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Ingår i: IEEE Transactions on Signal Processing. - : IEEE. - 1053-587X .- 1941-0476. ; 70, s. 3123-3135
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Tidskriftsartikel (refereegranskat)abstract
- Mean square error optimal estimation requires the full correlation structure to be available. Unfortunately, it is not always possible to maintain full knowledge about the correlations. One example is decentralized data fusion where the cross-correlations between estimates are unknown, partly due to information sharing. To avoid underestimating the covariance of an estimate in such situations, conservative estimation is one option. In this paper the conservative linear unbiased estimator is formalized including optimality criteria. Fundamental bounds of the optimal conservative linear unbiased estimator are derived. A main contribution is a general approach for computing the proposed estimator based on robust optimization. Furthermore, it is shown that several existing estimation algorithms are special cases of the optimal conservative linear unbiased estimator. An evaluation verifies the theoretical considerations and shows that the optimization based approach performs better than existing conservative estimation methods in certain cases.
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| 5. |
- Hedberg, Erik, et al.
(författare)
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A pedagogical path from the internal model principle to Youla-Kucera parametrization
- 2020
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Ingår i: IFAC PAPERSONLINE. - : ELSEVIER. - 2405-8963. ; , s. 17374-17379
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Konferensbidrag (refereegranskat)abstract
- We propose a sequence of pedagogical steps for introducing the Youla-Kucera parametrization, starting from the internal model principle, and introducing the control structures of disturbance observer and internal model control along the way. We provide some background on the concepts and a brief survey of their treatment in textbooks on control. Copyright (C) 2020 The Authors.
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| 6. |
- Hedberg, Erik, 1986-
(författare)
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Control, Models and Industrial Manipulators
- 2020
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The two topics at the heart of this thesis are how to improve control of industrial manipulators and how to reason about the role of models in automatic control.On industrial manipulators, two case studies are presented. The first investigates estimation with inertial sensors, and the second compares control by feedback linearization to control based on gain-scheduling.The contributions on the second topic illustrate the close connection between control and estimation in different ways. A conceptual model of control is introduced, which can be used to emphasize the role of models as well as the human aspect of control engineering. Some observations are made regarding block-diagram reformulations that illustrate the relation between models, control and inversion. Finally, a suggestion for how the internal model principle, internal model control, disturbance observers and Youla-Kucera parametrization can be introduced in a unified way is presented.
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| 7. |
- Ljungqvist, Oskar, 1990-
(författare)
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Motion planning and feedback control techniques with applications to long tractor-trailer vehicles
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- During the last decades, improved sensor and hardware technologies as well as new methods and algorithms have made self-driving vehicles a realistic possibility in the near future. At the same time, there has been a growing demand within the transportation sector to increase efficiency and to reduce the environmental impact related to transportation of people and goods. Therefore, many leading automotive and technology companies have turned their attention towards developing advanced driver assistance systems and self-driving vehicles.Autonomous vehicles are expected to have their first big impact in closed environments, such as mines, harbors, loading and offloading sites. In such areas, the legal requirements are less restrictive and the surrounding environment is more controlled and predictable compared to urban areas. Expected positive outcomes include increased productivity and safety, reduced emissions and the possibility to relieve the human from performing complex or dangerous tasks. Within these sites, tractor-trailer vehicles are frequently used for transportation. These vehicles are composed of several interconnected vehicle segments, and are therefore large, complex and unstable while reversing. This thesis addresses the problem of designing efficient motion planning and feedback control techniques for such systems.The contributions of this thesis are within the area of motion planning and feedback control for long tractor-trailer combinations operating at low-speeds in closed and unstructured environments. It includes development of motion planning and feedback control frameworks, structured design tools for guaranteeing closed-loop stability and experimental validation of the proposed solutions through simulations, lab and field experiments. Even though the primary application in this work is tractor-trailer vehicles, many of the proposed approaches can with some adjustments also be used for other systems, such as drones and ships.The developed sampling-based motion planning algorithms are based upon the probabilistic closed-loop rapidly exploring random tree (CL-RRT) algorithm and the deterministic lattice-based motion planning algorithm. It is also proposed to use numerical optimal control offline for precomputing libraries of optimized maneuvers as well as during online planning in the form of a warm-started optimization step.To follow the motion plan, several predictive path-following control approaches are proposed with different computational complexity and performance. Common for these approaches are that they use a path-following error model of the vehicle for future predictions and are tailored to operate in series with a motion planner that computes feasible paths. The design strategies for the path-following approaches include linear quadratic (LQ) control and several advanced model predictive control (MPC) techniques to account for physical and sensing limitations. To strengthen the practical value of the developed techniques, several of the proposed approaches have been implemented and successfully demonstrated in field experiments on a full-scale test platform. To estimate the vehicle states needed for control, a novel nonlinear observer is evaluated on the full-scale test vehicle. It is designed to only utilize information from sensors that are mounted on the tractor, making the system independent of any sensor mounted on the trailer.
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