2,737 research outputs found
Model predictive control techniques for hybrid systems
This paper describes the main issues encountered when applying model predictive control to hybrid processes. Hybrid model predictive control (HMPC) is a research field non-fully developed with many open challenges. The paper describes some of the techniques proposed by the research community to overcome the main problems encountered. Issues related to the stability and the solution of the optimization problem are also discussed. The paper ends by describing the results of a benchmark exercise in which several HMPC schemes were applied to a solar air conditioning plant.Ministerio de Eduación y Ciencia DPI2007-66718-C04-01Ministerio de Eduación y Ciencia DPI2008-0581
Formal Synthesis of Controllers for Safety-Critical Autonomous Systems: Developments and Challenges
In recent years, formal methods have been extensively used in the design of
autonomous systems. By employing mathematically rigorous techniques, formal
methods can provide fully automated reasoning processes with provable safety
guarantees for complex dynamic systems with intricate interactions between
continuous dynamics and discrete logics. This paper provides a comprehensive
review of formal controller synthesis techniques for safety-critical autonomous
systems. Specifically, we categorize the formal control synthesis problem based
on diverse system models, encompassing deterministic, non-deterministic, and
stochastic, and various formal safety-critical specifications involving logic,
real-time, and real-valued domains. The review covers fundamental formal
control synthesis techniques, including abstraction-based approaches and
abstraction-free methods. We explore the integration of data-driven synthesis
approaches in formal control synthesis. Furthermore, we review formal
techniques tailored for multi-agent systems (MAS), with a specific focus on
various approaches to address the scalability challenges in large-scale
systems. Finally, we discuss some recent trends and highlight research
challenges in this area
Efficient Control Approaches for Guaranteed Frequency Performance in Power Systems
Due to high penetration of renewable energy, converter-interfaced sources are increasing in power systems and degrading the grid frequency response. Synthetic inertia emulation and guaranteed primary frequency response is a challenging task. Still, there is high potential for application of highly controllable converter-interfaced devices to help performance. Renewable energy sources and demand side smart devices also need to be equipped with innovative frequency control approaches that contribute to frequency regulation operations.
First, the wind turbine generator is chosen to represent an example of a converter- interfaced source. An augmented system frequency response model is derived, including the system frequency response model and a reduced-order model of the wind turbine generator representing the supportive active power due to supplementary inputs. An output feedback observer-based control is designed to provide guaranteed frequency performance. System performance is analyzed for different short circuit ratio scenarios where a lower bound to guarantee the performance is obtained.
Second, the load side control for frequency regulation with its challenges is introduced. 5G technology and its potential application in smart grids are analyzed. The effect of communication delays and packet losses on inertia emulation are investigated to show the need of using improved communication infrastructure.
Third, a robust delay compensation for primary frequency control using fast demand response is proposed. Possible system structured uncertainties and communication delays are considered to limit frequency variations using the proposed control approach. An uncertain governor dead-band model is introduced to capture frequency response characteristics. Guaranteed inertial response is achieved and compared with a PI-based Smith predictor controller to show the effectiveness of the proposed method.
Fourth, set theoretic methods for safety verification to provide guaranteed frequency response are introduced. The Barrier certificate approach using a linear programming relaxation by Handelman’s representation is proposed with its application to power systems.
Finally, the Handelman’s based barrier certificate approach for adequate frequency performance is studied. The computational algorithm is provided for the proposed method and validated using power system benchmark case studies with a discussion on a safety supervisory control (SSC)
DESIGN OF OPTIMAL PROCEDURAL CONTROLLERS FOR CHEMICAL PROCESSES MODELLED AS STOCHASTIC DISCRETE EVENT SYSTEMS
This thesis presents a formal method for the the design of optimal and provably correct
procedural controllers for chemical processes modelled as Stochastic Discrete Event Systems
(SDESs). The thesis extends previous work on Procedural Control Theory (PCT) [1],
which used formal techniques for the design of automation Discrete Event Systems (DESs).
Many dynamic processes for example, batch operations and the start-up and shut down of
continuous plants, can be modelled as DESs. Controllers for these systems are typically
of the sequential type.
Most prior work on characterizing the behaviour of DESs has been restricted to deterministic
systems. However, DESs consisting of concurrent interacting processes present
a broad spectrum of uncertainty such as uncertainty in the occurrence of events. The
formalism of weighted probabilistic Finite State Machine (wp-FSM) is introduced for
modelling SDESs and pre-de ned failure models are embedded in wp-FSM to describe
and control the abnormal behaviour of systems. The thesis presents e cient algorithms
and procedures for synthesising optimal procedural controllers for such SDESs.
The synthesised optimal controllers for such stochastic systems will take into consideration
probabilities of events occurrence, operation costs and failure costs of events in
making optimal choices in the design of control sequences. The controllers will force the
system from an initial state to one or more goal states with an optimal expected cost and
when feasible drive the system from any state reached after a failure to goal states.
On the practical side, recognising the importance of the needs of the target end
user, the design of a suitable software implementation is completed. The potential of both
the approach and the supporting software are demonstrated by two industry case studies.
Furthermore, the simulation environment gPROMS was used to test whether the operating
speci cations thus designed were met in a combined discrete/continuous environment
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