Miguel A. Ridao

Model Predictive Control for power management in hybrid fuel cell vehicles

Fuel Cell Hybrid Electric Vehicles (FCHEV) are being investigated in many research and development programs motivated by the urgent need for more fuel-efficient vehicles that produce fewer harmful emissions. Hybridization can greatly benefit fuel cell technology. There are many potential advantages such as the improvement of transient power demand, the ability of regenerative braking and the opportunities for optimization of the vehicle efficiency. The coordination among the various power sources requires a high level of control in the vehicle.

Applying Risk Management to Combined Heat and Power Plants

This paper shows how risk management can be applied to schedule the operation of combined heat and power plants in order to consider process uncertainties. The main innovative point is the consideration of mitigation actions to reduce exposure to the identified risks. Model predictive control is used to select the strategic plan of mitigation actions.

Using a risk-based approach to project scheduling: A case illustration from semiconductor manufacturing

This paper introduces a risk-based optimization method to schedule projects. The method uses risk mitigation and optimal control techniques to minimize variables such as the project duration or the cost estimate at completion. Mitigation actions reduce the risk impacts that may affect the system. A model predictive control approach is used to determine the set of mitigation actions to be executed and the time in which they are taken. A real-life project in the field of semiconductor manufacturing has been taken as an example to show the benefits of the method in a deterministic case and a Monte Carlo simulation has also been carried out.

Constrained Predictive Control of an Irrigation Canal

AbstractThis paper presents the application of a distributed model predictive controller (DMPC) to the control of an accurate model of an actual irrigation canal in Spain. The canal is modeled using the Saint-Venant equations and implemented using the well-known Simulation of Irrigation Canals (SIC) modeling software for irrigation canals. The DMPC algorithm has been implemented in Matlab and interfaced to SIC. In the distributed-control algorithms, the local controllers exchange information so that their control policies are optimal in the sense of getting the best value of a performance index. The results show that the proposed distributed-control algorithm obtains better control performance than a more-conventional decentralized control scheme without information exchange. This better performance translates directly into money and resource savings.

A Risk-Based Model Predictive Control Approach to Adaptive Interventions in Behavioral Health

This brief examines how control engineering and risk management techniques can be applied in the field of behavioral health through their use in the design and implementation of adaptive behavioral interventions. Adaptive interventions are gaining increasing acceptance as a means to improve prevention and treatment of chronic, relapsing disorders, such as abuse of alcohol, tobacco, and other drugs, mental illness, and obesity. A risk-based model predictive control (MPC) algorithm is developed for a hypothetical intervention inspired by Fast Track, a real-life program whose long-term goal is the prevention of conduct disorders in at-risk children. The MPC-based algorithm decides on the appropriate frequency of counselor home visits, mentoring sessions, and the availability of after-school recreation activities by relying on a model that includes identifiable risks, their costs, and the cost/benefit assessment of mitigating actions. MPC is particularly suited for the problem because of its constraint-handling capabilities, and its ability to scale to interventions involving multiple tailoring variables. By systematically accounting for risks and adapting treatment components over time, an MPC approach as described in this brief can increase intervention effectiveness and adherence while reducing waste, resulting in advantages over conventional fixed treatment. A series of simulations are conducted under varying conditions to demonstrate the effectiveness of the algorithm.

Hierarchical distributed model predictive control for risk mitigation: An irrigation canal case study

This paper presents a hierarchical distributed model predictive control approach applied to irrigation canals planning from the point of view of risk mitigation. In the lower control level, a distributed model predictive controller manipulates flows and gate openings in order to follow the water level set-points indicated by the upper control level, which in addition executes mitigation actions if risk occurrences are expected. This work shows how model predictive control can be used as a decision tool which takes into account different types of risks, affecting the operation of irrigation canals.

An Evolutionary and Local Search Algorithm for Planning Two Manipulators Motion

A method based on the union of an Evolutionary Algorithm (EA) and a local search algorithm for obtaining coordinated motion plans of two manipulator robots is presented. A Decoupled Planning Approach has been used. For this purpose, the problem has been decomposed into two subproblems: path planning, where a collision-free path is found for each robot independently of the other, only considering fixed obstacles; and trajectory planning, where the paths are timed and synchronized in order to avoid collision with the other robot. This paper focuses on the second problem. A method is presented to minimize the total motion time of two manipulators along their paths, avoiding collision regardless of the accuracy of the dynamic model used. A hybrid technique with EA and local search methods has been implemented.

A DECISION SUPPORT SYSTEM FOR BIDDING PROCESS

Abstract This article has been developed in the frame of an IST European Project where Companies and Universities of several countries of Europe have collaborated. The work presents a Decision Support System (DSS) to provide help in the bidding process. Critical decisions as bid/no bid make/buy or decision of best final proposal have been realised. The tool performs a risk analysis and it uses the results in all the DSS phases.

Using Genetic Algorithms with Variable-length Individuals for Planning Two-Manipulators Motion

A method based on genetic algorithms for obtaining coordinated motion plans of manipulator robots is presented. A decoupled planning approach has been used; that is, the problem has been decomposed into two subproblems: path planning and trajectory planning. This paper focuses on the second problem. The generated plans minimize the total motion time of the robots along their paths. The optimization problem is solved by evolutionary algorithms using a variable-length individuals codification and specific genetic operators.

Optimal Operation of Pipeline Transportation Systems

Abstract This paper presents a simulator of an oil pipeline for scheduling purposes. The simulator includes an algorithm for optimizing the energy operating costs. The optimization algorithm works in two steps. The first one consists of the computation of a function that measures the estimated mininltun cost to the goal node. This computation involves the use of Bellmans optimality principle and of some heuristic rules in order to avoid the combinatorial explosion. During the second step the optinltmum trajectory is obtained with the help of the function mentioned above and using an accurate simulation of the transportation system. The simulation considers those aspects which are relevant t.o the optimization problem and takes into account the following factors: topology and topography of the network. non-linear characteristics of pumps and pipelines, variable demands of consumers, time changing prices of electrical energy and hydraulic equations throughout the system. The simulator is being used by CAMPSA (the major oil distribution company in Spain) Some results obtained with an oil pipeline system in Northern Spain are presented in the paper.