Model Predictive Path Planning of AGVs: Mixed Logical Dynamical Formulation and Distributed Coordination

Most of the existing path planning methods of automated guided vehicles (AGVs) are static. This paper proposes a new methodology for the path planning of a fleet of AGVs to improve the flexibility, robustness, and scalability of the AGV system. We mathematically describe the transport process as a dynamical system using an ad hoc mixed...

Distributed Leader-Follower Formation Control for Autonomous Vessels based on Model Predictive Control

Formation control of autonomous surface vessels (ASVs) has been studied extensively over the last few years since it offers promising advantages. In this paper, two control methods for distributed leader-follower formation control are proposed: A Nonlinear Model Predictive Control (MPC) method and an MPC method using Feedback Linearization. One...

A non-iterative cascaded predictive control approach for control of irrigation canals

Irrigation canals transport water from water sources (such as large rivers and lakes) to water users (such as farmers). Irrigation canals are typically very large in nature, covering vast geographical areas, and involving a significant number of control actuators, such as pumps, gates, and locks. The control of such canals is aimed at...

Multi-Area Predictive Control for Combined Electricity and Natural Gas Systems

The optimal operation of an integrated electricity and natural gas system is investigated. The couplings between these two systems are modeled by energy hubs, which serve as interface between the loads and the transmission infrastructures. Previously, we have applied a distributed control scheme to a static three-hub benchmark system. In this...

Coordinated model predictive reach control for irrigation canals

Irrigation canals are large-scale systems, covering vast geographical areas, and consisting of many interconnected canal reaches that interact with control structures such as pumps and gates. The control of such irrigation canals is usually done in a manual way, in which a human operator travels along the irrigation canal to adjust the settings...

Model-based predictive control applied to multi-carrier energy systems

The optimal operation of an integrated electricity and natural gas infrastructure is investigated. The couplings between the electricity system and the gas system are modeled by so-called energy hubs, which represent the interface between the loads on the one hand and the transmission infrastructures on the other. To increase reliability and...

Model predictive control of fuel cell micro cogeneration systems

With the increasing application of distributed energy resources and information technologies in the electricity infrastructure, innovative possibilities for incorporating the demand side more actively in power system operation are enabled. At the residential level energy costs could be reduced with intelligent price-based control concepts ...

Economic advantages of applying model predictive control to distributed energy resources: The case of micro-CHP systems

The increasing presence of distributed energy resources, information and intelligence in the electricity infrastructure increases the possibilities for larger economic efficiency of power systems. This work shows the possible cost advantages of applying a model predictive control (MPC) strategy to residential energy systems. MPC can take future...

Multi-agent model predictive control with applications to power networks

Transportation networks, such as power networks, road traffic networks, water distribution networks, railway networks, etc., are the corner stones of our modern society. As transportation networks have to operate closer and closer to their capacity limits and as the dynamics of these networks become more and more complex, control of these...

Multi-agent model predictive control for transportation networks with continuous and discrete elements

For several reasons, control of transportation networks like road traffic networks, power transmission networks, water distribution networks, etc. has to be done using a multi-agent control approach. We consider a multi-agent control approach in which each control agent uses Model Predictive Control (MPC) to determine its actions. Each control...

Challenges for process system engineering in infrastructure operation and control

The need for improving the operation and control of infrastructure systems has created a demand on optimization methods applicable in the area of complex sociotechnical systems operated by a multitude of actors in a setting of decentralized decision making. This paper briefly presents main classes of optimization models applied in PSE system...

Multi-agent model predictive control for transportation networks: Serial versus parallel schemes

We consider the control of large-scale transportation networks, like road traffic networks, power distribution networks, water distribution networks, etc. Control of these networks is often not possible from a single point by a single intelligent control agent; instead control has to be performed using multiple intelligent agents. We consider...

Experience-based model predictive control using reinforcement learning

Model predictive control (MPC) is becoming an increasingly popular method to select actions for controlling dynamic systems. TraditionallyMPC uses a model of the system to be controlled and a performance function to characterize the desired behavior of the system. The MPC agent finds actions over a finite horizon that lead the system into a...