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Li, Y., Feng, L. & Wang, Y. (2019). A cascade control approach to active suspension using pneumatic actuators. Asian journal of control, 1-19
Open this publication in new window or tab >>A cascade control approach to active suspension using pneumatic actuators
2019 (English)In: Asian journal of control, ISSN 1561-8625, E-ISSN 1561-8625, p. 1-19Article in journal (Refereed) Published
Abstract [en]

Operators of forest machinery suffer from intensive whole body vibrations, which are big threats to their health. Therefore, it is important to investigate effective seat undercarriages and control methods for vibration reduction. This paper addresses the control problem of a novel seat undercarriage with pneu-matic actuators customized for forest machinery. A two-layer cascade controlstructure is developed, where the top layer consists of a group of proportional controllers to regulate the position of pneumatic actuators and the bottom layeris a sliding mode controller for force and stiffness tracking. The advantage ofthe sliding mode control is to achieve robust control performance with coarse system models. The paper demonstrates that the proposed control structure is better than a traditional PID controller. The robust stability of the sliding mode controller is proved by the Lyapunov's method. Experiments show its capability of reducing at least 20% amplitude of seat vibrations from 0.5 to 1 Hz.

Place, publisher, year, edition, pages
Wiley, 2019
Keywords
active suspension, Lyapunov stability, pneumatic actuators, sliding mode control (SMC)
National Category
Fluid Mechanics and Acoustics
Research subject
Machine Design
Identifiers
urn:nbn:se:kth:diva-241135 (URN)10.1002/asjc.2028 (DOI)000462064800007 ()2-s2.0-85059694675 (Scopus ID)
Funder
XPRES - Initiative for excellence in production research
Note

QC 20190118

Available from: 2019-01-12 Created: 2019-01-12 Last updated: 2019-04-23Bibliographically approved
Zhang, H., Feng, L. & Li, Z. (2019). Control of Black-Box Embedded Systems by Integrating Automaton Learning and Supervisory Control Theory of Discrete-Event Systems. IEEE Transactions on Automation Science and Engineering, 1-14
Open this publication in new window or tab >>Control of Black-Box Embedded Systems by Integrating Automaton Learning and Supervisory Control Theory of Discrete-Event Systems
2019 (English)In: IEEE Transactions on Automation Science and Engineering, ISSN 1545-5955, E-ISSN 1558-3783, p. 1-14Article in journal (Refereed) Published
Abstract [en]

The paper presents an approach to the control of black-box embedded systems by integrating automaton learning and supervisory control theory (SCT) of discrete-event systems (DES), where automaton models of both the system and requirements are unavailable or hard to obtain. First, the system is tested against the requirements. If all the requirements are satisfied, no supervisor is needed and the process terminates. Otherwise, a supervisor is synthesized to enforce the system to satisfy the requirements. To apply SCT and automaton learning technologies efficiently, the system is abstracted to be a finite-discrete model. Then, a C* learning algorithm is proposed based on the classical L* algorithm to infer a Moore automaton describing both the behavior of the system and the conjunctive behavior of the system and the requirements. Subsequently, a supervisor for the system is derived from the learned Moore automaton and patched on the system. Finally, the controlled system is tested again to check the correctness of the supervisor. If the requirements are still not satisfied, a larger Moore automaton is learned and a refined supervisor is synthesized. The whole process iterates until the requirements hold in the controlled system. The effectiveness of the proposed approach is manifested through two realistic case studies.

Place, publisher, year, edition, pages
IEEE, 2019
Keywords
automaton learning algorithm, black-box embedded system, software testing, supervisory control theory
National Category
Control Engineering
Research subject
Industrial Information and Control Systems
Identifiers
urn:nbn:se:kth:diva-256054 (URN)10.1109/TASE.2019.2929563 (DOI)
Funder
XPRES - Initiative for excellence in production research
Note

QC 20190906

Supervisory control theory of DES cansynthesize maximally permissive supervisory controllers to ensurethe correctness of software-controlled processes. The application of supervisory control theory relies on automaton models ofthe plant and specifications; however, the required models areoften unavailable and difficult to obtain for black-box embeddedsystems. Automaton learning is an effective method for inferringmodels of black-box systems. This paper integrates the twotechnologies so that the supervisory control theory is applicableto the development of black-box embedded software systems. Theproposed approach is implemented in a toolchain that connectsautomaton learning algorithms, SCT, and testing algorithms viascripts. The obtained supervisor is implemented as a softwarepatch to monitor and control the original system online.

Available from: 2019-08-17 Created: 2019-08-17 Last updated: 2019-09-06Bibliographically approved
Sun, T., Lian, B., Song, Y. & Feng, L. (2019). Elasto-dynamic Optimization of A 5-DoF Parallel Kinematic Machine Considering Parameter Uncertainty. IEEE/ASME transactions on mechatronics
Open this publication in new window or tab >>Elasto-dynamic Optimization of A 5-DoF Parallel Kinematic Machine Considering Parameter Uncertainty
2019 (English)In: IEEE/ASME transactions on mechatronics, ISSN 1083-4435, E-ISSN 1941-014XArticle in journal (Refereed) Published
Abstract [en]

Geometric errors, vibration and elastic deformation are the main causes for inaccuracy of parallel kinematic machines (PKMs). Instead of tackling these inaccuracies after the prototype has been built, this paper proposes a design optimization method to minimize vibration and deformation considering the effects of geometric errors before constructing the PKM. In the presented study, geometric errors are described as parameter uncertainty because they are unknown in design stage. A 5 degree-of-freedom (DoF) PKM is taken to exemplify this method. Elasto-dynamic model is firstly formulated by a step-by-step strategy. On this basis, dynamic performances, including natural frequency, elastic deformation and maximum stress, are analyzed. These analytical results are verified by finite element simulation and experiment. Then, the necessity of concerning parameter uncertainty in optimization is addressed. Next, parameter uncertainty is added to the formulation of objectives and constraints by Monte Carlo simulation (MCS) and response surface method (RSM). Finally, elasto-dynamic optimization of the 5-DoF PKM is implemented to rebuild a prototype which is robust to geometric errors and has minimal vibration and deformation. The proposed method can also be applied to accuracy improvement of any machines in practical applications.

Keywords
accuracy improvement, parallel kinematic machine, design optimization, elasto-dynamic performance, parameter uncertainty
National Category
Other Mechanical Engineering
Research subject
Machine Design
Identifiers
urn:nbn:se:kth:diva-241140 (URN)10.1109/TMECH.2019.2891355 (DOI)
Funder
XPRES - Initiative for excellence in production research
Note

QC 20190129

Available from: 2019-01-14 Created: 2019-01-14 Last updated: 2019-01-29Bibliographically approved
Tao, S., Lian, B., Yimin, S. & Feng, L. (2019). Elasto-dynamicoptimization of a 5-DoF parallel kinematic machine considering parameteruncertainty. IEEE/ASME transactions on mechatronics (1), 315-325
Open this publication in new window or tab >>Elasto-dynamicoptimization of a 5-DoF parallel kinematic machine considering parameteruncertainty
2019 (English)In: IEEE/ASME transactions on mechatronics, ISSN 1083-4435, E-ISSN 1941-014X, no 1, p. 315-325Article in journal (Refereed) Published
Abstract [en]

Geometric errors, vibration, and elastic deformation are the main causes for inaccuracy of parallel kinematic machines (PKMs). Instead of tackling these inaccuracies after the prototype has been built, this paper proposes a design optimization method to minimize vibration and deformation considering the effects of geometric errors before constructing the PKM. In this paper, geometric errors are described as parameter uncertainty because they are unknown in design stage. A five degree-of-freedom (DoF) PKM is taken to exemplify this method. Elastodynamic model is first formulated by a step-by-step strategy. On this basis, dynamic performances, including natural frequency, elastic deformation, and maximum stress, are analyzed. These analytical results are verified by finite-element simulation and experiment. Then, the necessity of concerning parameter uncertainty in optimization is addressed. Next, parameter uncertainty is added to the formulation of objectives and constraints by Monte Carlo simulation and response surface method. Finally, elastodynamic optimization of the 5-DoF PKM is implemented to rebuild a prototype which is robust to geometric errors and has minimal vibration and deformation. The proposed method can also be applied to accuracy improvement of any machines in practical applications.

Place, publisher, year, edition, pages
IEEE, 2019
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-249502 (URN)10.1109/tmech.2019.2891355 (DOI)000458807900031 ()2-s2.0-85062077621 (Scopus ID)
Note

QC 20190507

Available from: 2019-04-12 Created: 2019-04-12 Last updated: 2019-05-07Bibliographically approved
Vahdati, P. M., Feng, L. & Törngren, M. (2018). Design Optimization of Cyber-Physical Systems by Partitioning and Coordination: A Study on Mechatronic Systems. In: Proceedings - 21st Euromicro Conference on Digital System Design, DSD 2018: . Paper presented at 21st Euromicro Conference on Digital System Design, DSD 2018, Prague, Czech Republic, 29 August 2018 through 31 August 2018 (pp. 304-311311). IEEE, Article ID 8491832.
Open this publication in new window or tab >>Design Optimization of Cyber-Physical Systems by Partitioning and Coordination: A Study on Mechatronic Systems
2018 (English)In: Proceedings - 21st Euromicro Conference on Digital System Design, DSD 2018, IEEE, 2018, p. 304-311311, article id 8491832Conference paper, Published paper (Refereed)
Abstract [en]

Cyber-Physical Systems are inherently complex. Reducing the design complexity of such systems, is beneficial for scalability of the design. In this paper, a method for design optimization of these systems is proposed to facilitate the decomposition of the optimization problem for the whole system into smaller sub-problems and coordination of modular solutions to reach the desired optimum. The coordinated solutions are either identical to the optimal solution of the complex optimization problem for the system as a whole or within an acceptable error margin of it. To demonstrate the efficacy of the method, it is applied to a mechatronic case study. The results provide evidence for the potential feasibility of the methodology in terms of meeting the requirements on the solutions, while reducing the computational demand of the design process.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
cyber-physical systems, mechatronic systems, design optimization, design structure matrix
National Category
Other Mechanical Engineering
Research subject
Machine Design
Identifiers
urn:nbn:se:kth:diva-240617 (URN)10.1109/DSD.2018.00061 (DOI)2-s2.0-85056487947 (Scopus ID)
Conference
21st Euromicro Conference on Digital System Design, DSD 2018, Prague, Czech Republic, 29 August 2018 through 31 August 2018
Projects
oCPSXPRES
Funder
EU, Horizon 2020, 674875XPRES - Initiative for excellence in production research, 674875
Note

QC 20190117

Available from: 2018-12-20 Created: 2018-12-20 Last updated: 2019-01-17Bibliographically approved
Liu, T., Feng, L., Hellgren, M. & Wikander, J. (2018). Increasing Fuel Efficiency of a Hybrid Electric Competition Car by a Binary Equivalent Consumption Minimization Strategy. In: 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE): . Paper presented at 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE). IEEE
Open this publication in new window or tab >>Increasing Fuel Efficiency of a Hybrid Electric Competition Car by a Binary Equivalent Consumption Minimization Strategy
2018 (English)In: 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE), IEEE, 2018Conference paper, Published paper (Refereed)
Abstract [en]

To improve the fuel efficiency of a hybrid electric car with special powertrain features racing in Shell Eco-marathon, a computationally efficient online control system is developed by solving hierarchical optimal control problems. The top-level computes the optimal velocity trajectory based on the given competition track in advance. The lower-level then finds the best instantaneous engine state and torque allocation by the equivalent consumption minimization strategy (ECMS). The special design of the competition car reduces the ECMS into a binary optimization problem. The new controller can run in real-time on low-cost microprocessors and improves the car's fuel efficiency by 50% while maintaining the state of charge of the electrical energy buffer.

Place, publisher, year, edition, pages
IEEE, 2018
National Category
Vehicle Engineering
Research subject
Machine Design
Identifiers
urn:nbn:se:kth:diva-240618 (URN)10.1109/COASE.2018.8560378 (DOI)2-s2.0-85059975846 (Scopus ID)
Conference
2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)
Funder
XPRES - Initiative for excellence in production research
Note

QC 20190109

Available from: 2018-12-20 Created: 2018-12-20 Last updated: 2019-03-20Bibliographically approved
Svensson, L., Masson, L., Mohan, N., Ward, E., Pernestål Brenden, A., Feng, L. & Törngren, M. (2018). Safe Stop Trajectory Planning for Highly Automated Vehicles:An Optimal Control Problem Formulation. In: 2018 IEEE Intelligent Vehicles Symposium (IV): . Paper presented at 2018 IEEE Intelligent Vehicles Symposium, IV 2018; Changshu, Suzhou; China; 26 September 2018 through 30 September 2018 (pp. 517-522). Institute of Electrical and Electronics Engineers (IEEE), Article ID 8500536.
Open this publication in new window or tab >>Safe Stop Trajectory Planning for Highly Automated Vehicles:An Optimal Control Problem Formulation
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2018 (English)In: 2018 IEEE Intelligent Vehicles Symposium (IV), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 517-522, article id 8500536Conference paper, Published paper (Refereed)
Abstract [en]

Highly automated road vehicles need the capabilityof stopping safely in a situation that disrupts continued normaloperation, e.g. due to internal system faults. Motion planningfor safe stop differs from nominal motion planning, since thereis not a specific goal location. Rather, the desired behavior isthat the vehicle should reach a stopped state, preferably outsideof active lanes. Also, the functionality to stop safely needs tobe of high integrity. The first contribution of this paper isto formulate the safe stop problem as a benchmark optimalcontrol problem, which can be solved by dynamic programming.However, this solution method cannot be used in real-time. Thesecond contribution is to develop a real-time safe stop trajectoryplanning algorithm, based on selection from a precomputedset of trajectories. By exploiting the particular properties ofthe safe stop problem, the cardinality of the set is decreased,making the algorithm computationally efficient. Furthermore, amonitoring based architecture concept is proposed, that ensuresdependability of the safe stop function. Finally, a proof of conceptsimulation using the proposed architecture and the safe stoptrajectory planner is presented.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
National Category
Robotics
Identifiers
urn:nbn:se:kth:diva-232815 (URN)10.1109/IVS.2018.8500536 (DOI)2-s2.0-85056784560 (Scopus ID)9781538644522 (ISBN)
Conference
2018 IEEE Intelligent Vehicles Symposium, IV 2018; Changshu, Suzhou; China; 26 September 2018 through 30 September 2018
Note

QC 20180806

Available from: 2018-08-02 Created: 2018-08-02 Last updated: 2019-05-22Bibliographically approved
Rashidinejad, A., Reniers, M. & Feng, L. (2018). Supervisory Control of Timed Discrete-Event Systems Subject to Communication Delays and Non-FIFO Observations. Paper presented at 14th IFAC International Workshop on Discrete Event Systems (WODES), MAY 30-JUN 01, 2018, ITALY. IFAC PAPERSONLINE, 51(7), 456-463
Open this publication in new window or tab >>Supervisory Control of Timed Discrete-Event Systems Subject to Communication Delays and Non-FIFO Observations
2018 (English)In: IFAC PAPERSONLINE, ISSN 2405-8963, Vol. 51, no 7, p. 456-463Article in journal (Refereed) Published
Abstract [en]

Conventional supervisory control synthesis techniques are not adequate anymore when a network between the plant and the supervisor introduces communication delays. This paper presents a method to synthesize a networked supervisor handling delays in both observation and control channels. To deal with the problem of delayed observations, we propose an automaton modeling the behaviour of the plant observed by a supervisor through a network, called observed plant. In this automaton, events observed by a supervisor are delayed from those occurring in the plant. Moreover, since observation channels are considered not to have the first in first out (FIFO) characteristic, events may not be necessarily observed in the same order as they occurred within the plant. A safe, observable, controllable and nonblocking supervisor is synthesized for the observed plant by means of an adapted synthesis algorithm for timed discrete-event systems (TDES). By enabling the achieved supervisor to predict the effects of control delays, it will be further transformed to a networked supervisor. The networked supervisor makes decisions ahead of time to ensure that the commands will be applied on the right (plant) state.

Place, publisher, year, edition, pages
Elsevier, 2018
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:kth:diva-232930 (URN)10.1016/j.ifacol.2018.06.340 (DOI)000439161000072 ()2-s2.0-85050100687 (Scopus ID)
Conference
14th IFAC International Workshop on Discrete Event Systems (WODES), MAY 30-JUN 01, 2018, ITALY
Note

QC 20180807

Available from: 2018-08-07 Created: 2018-08-07 Last updated: 2018-08-07Bibliographically approved
Zhang, X., Song, X., Feng, L., Chen, L. & Törngren, M. (2017). A Case Study on Achieving Fair Data Age Distribution in Vehicular Communications. In: Parmer, G (Ed.), PROCEEDINGS OF THE 23RD IEEE REAL-TIME AND EMBEDDED TECHNOLOGY AND APPLICATIONS SYMPOSIUM (RTAS 2017): . Paper presented at 23rd IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), APR 18-21, 2017, Pittsburgh, PA (pp. 307-317). IEEE
Open this publication in new window or tab >>A Case Study on Achieving Fair Data Age Distribution in Vehicular Communications
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2017 (English)In: PROCEEDINGS OF THE 23RD IEEE REAL-TIME AND EMBEDDED TECHNOLOGY AND APPLICATIONS SYMPOSIUM (RTAS 2017) / [ed] Parmer, G, IEEE , 2017, p. 307-317Conference paper, Published paper (Refereed)
Abstract [en]

In vehicular communication protocol stacks, received messages may not always be decoded successfully due to the complexity of the decoding functions, the uncertainty of the communication load and the limited computation resources. Even worse, an improper implementation of the protocol stack may cause an unfair data age distribution among all the communicating vehicles (the receiving bias problem). In such cases, some vehicles are almost locked out of the vehicular communication, causing potential safety risk in scenarios such as intersection passing. To our knowledge, this problem has not been systematically studied in the fields of vehicular communication and intelligent transport systems (ITS). This paper analyzes the root of the receiving bias problem and proposes architectural solutions to balance data age distribution. Simulation studies based on commercial devices demonstrate the effectiveness of these solutions. In addition, our system has been successfully applied during the Grand Cooperative Driving Challenge, where complicated scenarios involving platooning maneuvering and intersection coordination were conducted.

Place, publisher, year, edition, pages
IEEE, 2017
Series
IEEE Real-Time and Embedded Technology and Applications Symposium, ISSN 1545-3421
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:kth:diva-215487 (URN)10.1109/RTAS.2017.7 (DOI)000411195100034 ()2-s2.0-85021802444 (Scopus ID)978-1-5090-5269-1 (ISBN)
Conference
23rd IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), APR 18-21, 2017, Pittsburgh, PA
Note

QC 20171013

Available from: 2017-10-13 Created: 2017-10-13 Last updated: 2019-04-15Bibliographically approved
Khodabakhshian, M., Feng, L., Börjesson, S., Lindgärde, O. & Wikander, J. (2017). Reducing Auxiliary Energy Consumption of Heavy Trucks by Onboard Prediction and Real-time Optimization. Applied Energy, 188, 652-671
Open this publication in new window or tab >>Reducing Auxiliary Energy Consumption of Heavy Trucks by Onboard Prediction and Real-time Optimization
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2017 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 188, p. 652-671Article in journal (Refereed) Published
Abstract [en]

The electric engine cooling system, where the coolant pump and the radiator fan are driven by electric motors, admits advanced control methods to decrease auxiliary energy consumption. Recent publications show the fuel saving potential of optimal control strategies for the electric cooling system through offline simulations. These strategies often assume full knowledge of the drive cycle and compute the optimal control sequence by expensive global optimization methods. In reality, the full drive cycle is unknown during driving and global optimization not directly applicable on resource-constrained truck electronic control units. This paper reports state-of-the-art engineering achievements of exploiting vehicular onboard prediction for a limited time horizon and minimizing the auxiliary energy consumption of the electric cooling system through real-time optimization. The prediction and optimization are integrated into a model predictive controller (MPC), which is implemented on a dSPACE MicroAutoBox and tested on a truck on a public road. Systematic simulations show that the new method reduces fuel consumption of a 40-tonne truck by 0.36% and a 60-tonne truck by 0.69% in a real drive cycle compared to a base-line controller. The reductions on auxiliary fuel consumption for the 40-tonne and 60-tonne trucks are about 26% and 38%, respectively. Truck experiments validate the consistency between simulations and experiments and confirm the real-time feasibility of the MPC controller. © 2016 Elsevier Ltd

Place, publisher, year, edition, pages
Elsevier, 2017
Keywords
Engine cooling system; Model predictive control (MPC); Parasitic load reduction; Quadratic programming (QP)
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:kth:diva-181077 (URN)10.1016/j.apenergy.2016.11.118 (DOI)000393003100053 ()2-s2.0-85007038221 (Scopus ID)
Projects
CONVENIENT
Funder
EU, FP7, Seventh Framework Programme, 312314
Note

QC 20170111

Available from: 2016-01-28 Created: 2016-01-28 Last updated: 2017-05-22Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-5703-5923

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