Economic Model Predictive Controllers, consisting of an economic criterion as stage cost for the dynamic regulation problem, have shown to improve the economic performance of the controlled plant, as ...well as to ensure stability of the economic setpoint. However, throughout the operation of the plant, economic criteria are usually subject to frequent changes, due to variations of prices, costs, production demand, market fluctuations, reconciled data, disturbances, etc. A different economic criterion determines a change of the optimal operation point and this may cause a loss of feasibility and/or stability. In this paper a stabilizing economic MPC for changing economic criterion for linear prediction models is presented. The proposed controller always ensures feasibility for any given economic criterion, thanks to the particular choice of the terminal ingredients. Asymptotic stability is also proved, providing a Lyapunov function.
•Centralized MPC that maximizes the thermal power of a parabolic-trough field.•Distributed MPC that approaches the Centralized MPC and can be computed in real-time.•The use of valves at each loop can ...significantly increase the achieved thermal power.•Higher outlet temperatures do not imply a larger energy production.
This paper proposes a new centralized Model Predictive Control (MPC) algorithm for the maximization of the thermal power obtained with a parabolic-trough collector field. The optimal operation of the plant is achieved by controlling a set of valves located at the beginning of each loop of collectors, which allow to outperform the response achieved with traditional control approaches for parabolic-trough plants.
Unfortunately, the computational complexity of the proposed MPC controller hinders its application in real-time for medium and large parabolic-trough power plants. Consequently, this paper also proposes a logic-based distributed Model Predictive Control algorithm, which approaches the performance of the centralized MPC but entailing a much lower computational load.
The proposed controllers are tested by simulation using a model of the collector field ACUREX (Almería, Spain) along a 2-h synthetic DNI profile. The results obtained show that the proposed distributed algorithm is able to perform quite close to the centralized one. Moreover, the analysis of the numerical results (in terms of achieved power) shows that the use of valves at the beginning of each loop substantially improve the achieved thermal power, that the achieved performance using a local controller is significantly lower than using a global one, and that the maximization of the thermal power does not imply the maximization or minimization of the outlet temperature.
In this article, a coalitional robust model predictive controller for tracking target sets is presented. The overall system is controlled by a set of local control agents that dynamically merge into ...cooperative coalitions or clusters so as to attain an efficient tradeoff between cooperation burden and global performance optimality. Within each cluster, the agents coordinate their inputs to maximize their collective performance, while considering the coupling effect with external subsystems as uncertainty. By using a tube-based approach, the overall system state is driven to the target sets while satisfying state and input constraints despite the changes in the controllers' clustering. Likewise, feasibility and stability of the closed-loop system are guaranteed by tracking techniques. The applicability of the proposed approach is illustrated by an academic example.
This paper presents a new approach for guaranteed state estimation based on zonotopes for linear discrete-time multivariable systems with interval multiplicative uncertainties, in the presence of ...bounded state perturbations and noises. At each sample time, the presented approach computes a zonotope which contains the real system state. A P-radius-based criterion is minimized in order to decrease the size of the zonotope at each sample time and to obtain an increasingly accurate state estimation. The proposed approach allows one to efficiently handle the trade-off between the complexity of the computation and the accuracy of the estimation. An illustrative example is analyzed in order to highlight the advantages of the proposed state estimation technique.
•Control by clustering for maximizing the thermal power of solar fields.•Valves at the beginning of each loop increase the achieved thermal power.•The clustering criterion is to associate unbalanced ...loops dynamically.•Coalitional MPC approaches the optimal performance and can be carried in real-time.•Scalability and ease of deployment in large-scale CSP fields.
This article shows how coalitional model predictive control (MPC) can be used to maximize thermal power of large-scale solar parabolic-trough plants. This strategy dynamically generates clusters of loops of collectors according to a given criterion, thus dividing the plant into loosely coupled subsystems that are locally controlled by their corresponding loop valves to gain performance and speed up the computation of control inputs. The proposed strategy is assessed with decentralized and centralized MPC in two simulated solar parabolic-trough fields. Finally, results regarding scalability are also given using these case studies.
A novel aircraft path-following guidance algorithm based on model predictive control is proposed in this paper. The algorithm tracks a precomputed trajectory and produces reference commands for a ...low-level attitude controller. To solve the associated nonlinear optimization problem, an iterative scheme is proposed, using as a feasible hotstart the guidance solution provided by a well-behaved L1 navigation law. Simulations show the effectiveness of the algorithm, even in the presence of disturbances such as wind.
This paper discusses the application of coalitional model predictive control (MPC) to freeways traffic networks, where the goal is reducing the time spent by the drivers through a dynamic setting of ...variable speed limits (VSL) and ramp metering. The prediction model METANET is used to represent the traffic flows evolution. The system behavior and objective function lead to a non-convex and non-linear optimization problem, which can only be solved in a centralized fashion for small networks. The underlying motivation of this paper is the continued advance of clustering methods in the control of large-scale and spatially distributed systems. The global freeway system is partitioned into a set of coupled sub-stretches, which in turn are assigned to the different agents involved in the control problem. These local controllers can dynamically assemble into coalitions to take coordinated measures. In this work, a top-down approach is considered: the bottom layer consists of the set of controllers that compute the VSL and ramp-metering across time; and the supervisory layer changes periodically the information exchange structure to promote coalitions of those controllers that bring greater performance to the global system. In this way, a balance is sought between optimality and efficiency. Finally, the coalitional approach is simulated on a stretch of traffic freeway where cooperation with adjacent sub-stretches is allowed.
Coalitional Control for Self-Organizing Agents Fele, Filiberto; Debada, Ezequiel; Maestre, Jose Maria ...
IEEE transactions on automatic control,
09/2018, Letnik:
63, Številka:
9
Journal Article
Recenzirano
Odprti dostop
Coalitional control is concerned with the management of multi-agent systems where cooperation cannot be taken for granted (due to, e.g., market competition, logistics). This paper proposes a model ...predictive control (MPC) framework aimed at large-scale dynamically coupled systems whose individual components, possessing a limited model of the system, are controlled independently, pursuing possibly competing objectives. The emergence of cooperating clusters of controllers is contemplated through an autonomous negotiation protocol, based on the characterization as a coalitional game of the benefit derived by a broader feedback and the alignment of the individual objectives. Specific mechanisms for the cooperative benefit redistribution that relax the cognitive requirements of the game are employed to compensate for possible local cost increases due to cooperation. As a result, the structure of the overall MPC feedback can be adapted online to the degree of interaction between different parts of the system while satisfying the individual interests of the agents. A wide-area control application for the power grid with the objective of minimizing frequency deviations and undesired interarea power transfers is used as a study case.
Dead-time compensators: A survey Normey-Rico, Julio E.; Camacho, Eduardo. F.
Control engineering practice,
04/2008, Letnik:
16, Številka:
4
Journal Article
Recenzirano
This paper presents a review of the main dead-time compensators (DTC) described in literature. The paper analyses the basic Smith predictor (SP) showing its advantages and drawbacks. DTC structures ...designed to improve closed-loop characteristics and to control unstable systems are described. The paper concludes with some recommendations for designing dead-time compensator controllers.
This article focuses on maximizing the thermal energy collected by parabolic-trough solar collector fields to increase the production of the plant. To this end, we propose a market-based clustering ...model predictive control strategy in which controllers of collector loops may offer and demand heat transfer fluid in a market. When a transaction is made between loop controllers, a coalition is formed, and the corresponding agents act as a single entity. The proposed hierarchical algorithm fosters the formation of coalitions dynamically to improve the overall control objective, increasing the thermal energy delivered by the field. Finally, the proposed controller is assessed via simulation with other control methods in two solar parabolic-trough fields. The results show that the energy efficiency with the clustering strategy outperforms by 12% that of traditional controllers, and the method is implementable in real-time to control large-scale solar collector fields, where significant gains in thermal collected energy can be obtained, due to its scalability.
•Clustering of controllers to maximize the energy produced by solar collector fields.•Loop controllers can demand and offer heat transfer fluid in a flow market.•Coalitions of loops are promoted dynamically to reach the control objective.•Improvements of thermal energy efficiency by up to 12%.•Feasible real-time implementation in large-scale fields due to its superior scalability.
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