| 1. |
- 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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| 2. |
- Coimbatore Anand, Sribalaji, et al.
(författare)
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Risk-averse controller design against data injection attacks on actuators for uncertain control systems
- 2022
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Ingår i: 2022 AMERICAN CONTROL CONFERENCE (ACC). - : IEEE. - 9781665451963 ; , s. 5037-5042
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Konferensbidrag (refereegranskat)abstract
- In this paper, we consider the optimal controller design problem against data injection attacks on actuators for an uncertain control system. We consider attacks that aim at maximizing the attack impact while remaining stealthy in the finite horizon. To this end, we use the Conditional Value-at-Risk to characterize the risk associated with the impact of attacks. The worst-case attack impact is characterized using the recently proposed output-to-output l(2)-gain (OOG). We formulate the design problem and observe that it is non-convex and hard to solve. Using the framework of scenariobased optimization and a convex proxy for the OOG, we propose a convex optimization problem that approximately solves the design problem with probabilistic certificates. Finally, we illustrate the results through a numerical example.
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| 3. |
- Hellander, Anja, et al.
(författare)
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On a Traveling Salesman Problem with Dynamic Obstacles and Integrated Motion Planning
- 2022
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Ingår i: 2022 AMERICAN CONTROL CONFERENCE (ACC). - : IEEE. - 9781665451963 - 9781665494809 ; , s. 4965-4972
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Konferensbidrag (refereegranskat)abstract
- This paper presents a variant of the Traveling Salesman Problem (TSP) with nonholonomic constraints and dynamic obstacles, with optimal control applications in the mining industry. The problem is discretized and an approach for solving the discretized problem to optimality is proposed. The proposed approach solves the three subproblems (waypoint ordering, heading at each waypoint and motion planning between waypoints) simultaneously using two nested graph-search planners. The higher-level planner solves the waypoint ordering and heading subproblems while making calls to the lower-level planner that solves the motion planning subproblem using a lattice-based motion planner. For the higher-level motion planner A* search is used and two different heuristics, a minimal spanning tree heuristic and a nearest insertion heuristic, are proposed and optimality bounds are proven. The proposed planner is evaluated on numerical examples and compared to Dijkstras algorithm. Furthermore, the performance and observed suboptimality are investigated when the minimal spanning tree heuristic cost is inflated.
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| 4. |
- Kjellqvist, Olle, et al.
(författare)
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Minimax Adaptive Estimation for Finite Sets of Linear Systems
- 2022
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Ingår i: IEEE Xplore. - 9781665451963 - 9781665494809
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Konferensbidrag (refereegranskat)abstract
- For linear time-invariant systems with uncertain parameters belonging to a finite set, we present a purely eterministic approach to multiple-model estimation and propose an algorithm based on the minimax criterion using constrained quadratic programming. The estimator tends to learn the dynamics of the system, and once the uncertain parameters have been sufficiently estimated, the estimator behaves like a standard Kalman filter.
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| 5. |
- Naha, Arunava, et al.
(författare)
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Sequential Detection of Replay Attacks with a Parsimonious Watermarking Policy
- 2022
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Ingår i: 2022 American Control Conference (ACC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665451963 - 9781665494809 - 9781665451970 ; , s. 4868-4875
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Konferensbidrag (refereegranskat)abstract
- In this paper, we have proposed a technique for Bayesian sequential detection of replay attacks on networked control systems with a constraint on the average number of watermarking (ANW) events used during normal system operations. Such a constraint limits the increase in the control cost due to watermarking. To determine the optimal sequence regarding the addition or otherwise of watermarking signals, first, we formulate an infinite horizon stochastic optimal control problem with a termination state. Then applying the value iteration approach, we find an optional policy that minimizes the average detection delay (ADD) for fixed upper bounds on the false alarm rate (FAR) and ANW. The optimal policy turns out to be a two thresholds policy on the posterior probability of attack. We derive approximate expressions of ADD and FAR as functions of the two derived thresholds and a few other parameters. A simulation study on a single-input single-output system illustrates that the proposed method improves the control cost considerably at the expense of small increases in ADD. We also perform simulation studies to validate the derived theoretical results.
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| 6. |
- Shoja, Shamisa, Biträdande professor, 1991-, et al.
(författare)
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Overall Complexity Certification of a Standard Branch and Bound Method for Mixed-Integer Quadratic Programming
- 2022
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Ingår i: 2022 AMERICAN CONTROL CONFERENCE (ACC). - Atlanta, GA, USA : IEEE. - 9781665451963 - 9781665494809 ; , s. 4957-4964
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Konferensbidrag (refereegranskat)abstract
- This paper presents a method to certify the computational complexity of a standard Branch and Bound method for solving Mixed-Integer Quadratic Programming (MIQP) problems defined as instances of a multi-parametric MIQP. Beyond previous work, not only the size of the binary search tree is considered, but also the exact complexity of solving the relaxations in the nodes by using recent results from exact complexity certification of active-set QP methods. With the algorithm proposed in this paper, a total worst-case number of QP iterations to be performed in order to solve the MIQP problem can be determined as a function of the parameter in the problem. An important application of the proposed method is Model Predictive Control for hybrid systems, that can be formulated as an MIQP that has to be solved in real-time. The usefulness of the proposed method is successfully illustrated in numerical examples.
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| 7. |
- Tosun, Fatih Emre, et al.
(författare)
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Detection of Bias Injection Attacks on the Glucose Sensor in the Artificial Pancreas Under Meal Disturbance
- 2022
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Ingår i: 2022 AMERICAN CONTROL CONFERENCE (ACC). - : IEEE. - 9781665451963 ; , s. 1398-1405
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Konferensbidrag (refereegranskat)abstract
- The artificial pancreas is an emerging concept of closed-loop insulin delivery that aims to tightly regulate the blood glucose levels in patients with type 1 diabetes. This paper considers bias injection attacks on the glucose sensor deployed in an artificial pancreas. Modern glucose sensors transmit measurements through wireless communication that are vulnerable to cyber-attacks, which must be timely detected and mitigated. To this end, we propose a model-based anomaly detection scheme using a Kalman filter and a chi(2) test. One key challenge is to distinguish cyber-attacks from large unknown disturbances arising from meal intake. This challenge is addressed by an online meal estimator, and a novel time-varying detection threshold. More precisely, we show that the ordinary least squares is the optimal unbiased estimator of the meal size under certain modelling assumptions. Moreover, we derive a novel time-varying threshold for the chi(2) detector to avoid false alarms during meal ingestion. The results are validated by means of numerical simulations.
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