Jonas Balderud

Autonomous and decentralized mission planning for clusters of UUVs

This paper proposes an algorithm for autonomous strategic mission planning of missions where multiple unhabitated underwater vehicles (UUVs) cooperate in order to solve one or more mission tasks. Missions of this type include multi-agent reconnaissance missions and multi-agent mine sweeping missions. The mission planning problem is posed as a receding horizon mixed–integer constrained quadratic optimal control problem. This problem is subsequently partitioned into smaller subproblems and solved in a parallel and decentralized manner using a distributed Nash-based game approach. The paper presents the development of the proposed algorithm and discusses its properties. An application example is used to further demonstrate the main characteristics of the proposed method.

Distributed control of underwater vehicles

Despite the closed-loop performance of centralized multi-variable controllers, the vast majority of control applications are still based on decentralized controllers. Because of their single-loop structure, decentralized controllers cannot suppress interactions of the system, which are only taken into account in the controller tuning phase. Therefore, it would be useful in many cases to tackle the undesirable effects of the interactions on the closed-loop system. A novel model predictive control scheme based on Nash optimality is presented to achieve this goal. In this algorithm the centralized optimization is decomposed into that of several small coupled optimization problems. The relevant computational convergence, the closed-loop performance, and the effect of communication failures on the closed-loop behaviour are analysed. The control problem is illustrated to verify the effectiveness and practicality of the proposed control algorithm.

Multivariable PID control of an Activated Sludge Wastewater Treatment Process

In general, wastewater treatment plant (WWTP) consists of several stages before it is released to a receiving water body. There are, preliminary and primary treatment (mechanical treatment), a secondary treatment (biological treatment) and a tertiary treatment (chemical treatment). In this chapter, since the work involve of identification and control design of activated sludge process to improve the performance of the system, and most of the control priorities are centred on the biological treatment process, only the secondary treatment will be highlighted.

A control and monitoring oriented model of a film manufacturing process

Abstract This paper describes the development of a control and monitoring oriented model of a plastic film manufacturing process. The model is mainly derived from first-principles and has been implemented in the Matlab/Simulink dynamic simulation environment. The development of the model forms the first phase of a project that aims to develop a nonlinear sub-space based monitoring, fault detection and trouble shooting system for the film manufacturing process.

AUTONOMOUS CONTROL OF CLUSTERS OF UUVS

Abstract This paper is concenred with the development of control strategies for autonomous mission planning of a multiple Unhabitated Underwater Vehicles (UUVs) that cooperate in order to perform a number of tasks. Missions of this type include multi-agent reconnaissance and multi-agent mine sweeping problems. The mission planning problem is posed as a receding horizon mixed-integer constrained model based predictive control problem. This is subsequently partitioned into smaller subproblems and solved in a decentralised manner using a distributed Nash-based game approach. The paper presents further development of the method and gives a detailed example to demonstrate the main features of the control method and its implementation.

Distributed control design for underwater vehicles

The vast majority of control applications are based on non-interacting decentralized control designs. Because of their single-loop structure, these controllers cannot suppress interactions of the system. It would be useful to tackle the undesirable effects of the interactions at the design stage. A novel model predictive control scheme based on Nash optimality is presented to achieve this goal. In this algorithm, the control problem is decomposed into that of several small-coupled mixed integer optimisation problems. The relevant computational convergence, closed-loop performance and the effect of communication failures on the closed-loop behaviour are analysed. Simulation results are presented to illustrate the effectiveness and practicality of the proposed control algorithm.