A. Pedro Aguiar

A Framework for Structural Input/Output and Control Configuration Selection in Large-Scale Systems

This paper addresses problems on the structural design of large-scale control systems. An efficient and unified framework is proposed to select the minimum number of manipulated/measured variables to achieve structural controllability/observability of the system, and to select the minimum number of feedback interconnections between measured and manipulated variables such that the closed-loop system has no structural fixed modes. Global solutions are computed using polynomial complexity algorithms in the number of the state variables of the system. Finally, graph-theoretic characterizations are proposed, which allow a characterization of all possible solutions.

Path-following or reference tracking?: An answer relaxing the limits to performance

Abstract In path-following the control objective is to force the output to follow a geometric path without a timing law assigned to it. We highlight a fundamental difference between the path-following and the standard reference-tracking by demonstrating that performance limitation due to unstable zero-dynamics can be removed in the path-following problem.

A structured systems approach for optimal actuator-sensor placement in linear time-invariant systems

In this paper we address the actuator/sensor allocation problem for linear time invariant (LTI) systems. Given the structure of an autonomous linear dynamical system, the goal is to design the structure of the input matrix (commonly denoted by B) such that the system is structurally controllable with the restriction that each input be dedicated, i.e., it can only control directly a single state variable. We provide a methodology to determine the minimum number of dedicated inputs required to ensure structural controllability, and characterize all (when not unique) possible configurations of the minimal input matrix B. Furthermore, we show that the proposed solution incurs polynomial complexity in the number of state variables. By duality, the solution methodology may be readily extended to the structural design of the corresponding minimal output matrix (commonly denoted by C) that ensures structural observability.

Switched seesaw control for the stabilization of underactuated vehicles

This paper addresses the stabilization of a class of nonlinear systems in the presence of disturbances, using switching controllers. To this effect we introduce two new classes of switched systems and provide conditions under which they are input-to-state practically stable (ISpS). By exploiting these results, a methodology for control systems design-called switched seesaw control-is obtained that allows for the development of nonlinear control laws yielding input-to-state stability. The range of applicability and the efficacy of the methodology proposed are illustrated via two nontrivial design examples. Namely, stabilization of the extended nonholonomic double integrator (ENDI) and stabilization of an underactuated autonomous underwater vehicle (AUV) in the presence of input disturbances and measurement noise.

Multiple model adaptive wave filtering for dynamic positioning of marine vessels

This paper addresses a filtering problem that arises in the design of dynamic positioning systems for ships and offshore rigs subjected to the influence of sea waves. Its key contribution is twofold: i) it introduces an improved model for filter design, and ii) and it exploits the structure of a multiple model adaptive wave filter that relies on measurements of the vessels position and heading only. Namely, an improvement in the control plant model is proposed that better captures the physics of the problem at hand and a bank of Kalman filters is designed for a finite number of parameter values, each corresponding to a different peak frequency of the assumed wave spectrum model. Tools from multiple model adaptive estimation (MMAE) theory are exploited to blend the information provided by the different observers, yielding position and velocity estimates of the marine vessel. These estimates are then to be used in an appropriately designed feedback control law. Simulations illustrate the efficacy of the MMAE techniques proposed and the improvement in performance that is obtained when compared with other approaches.

Optimal Control on Lie Groups: The Projection Operator Approach

Many nonlinear systems of practical interest evolve on Lie groups or on manifolds acted upon by Lie groups. Examples range from aircraft and underwater vehicles to quantum mechanical systems. In this paper, we develop an algorithm for solving continuous-time optimal control problems for systems evolving on (noncompact) Lie groups. This algorithm generalizes the projection operator approach for trajectory optimization originally developed for systems on vector spaces. Notions for generalizing system theoretic tools such as Riccati equations and linear and quadratic system approximations are developed. In this development, the covariant derivative of a map between two manifolds plays a key role in providing a chain rule for the required Lie group computations. An example optimal control problem on SO(3) is provided to highlight implementation details and to demonstrate the effectiveness of the method.

Joint ASV/AUV range-based formation control: Theory and experimental results

The use of groups of autonomous marine vehicles has enormous potential in numerous marine applications, perhaps the most relevant of which is the surveying and exploration of the oceans, still widely unknown and misunderstood. In many mission scenarios requiring the concerted operation of multiple marine vehicles carrying distinct, yet complementary sensor suites, relative positioning and formation control becomes mandatory. However, the constraints placed by the medium make it hard to both communicate and localize vehicles, even in relation to each other. In this paper, we deal with the challenging problem of keeping an autonomous underwater vehicle in a moving triangular formation with respect to 2 leader vehicles. We build upon our previous theoretical work on range-only formation control, which presents simple feedback laws to drive the controlled vehicle to its intended position in the formation using only ranges obtained to the leading vehicles with no knowledge of the formation path. We then introduce the real-world constraints associated with the use of autonomous underwater vehicles, especially the low frequency characteristics of acoustic ranging and its unreliability. We discuss the required changes to implement the solution in our vehicles, and provide simulation results using a full dynamic and communication model. Finally, we present the results of real world trials using MEDUSA-class autonomous marine vehicles.

Multiple Model Adaptive Estimation and model identification usign a Minimum Energy criterion

This paper addresses the problem of Multiple Model Adaptive Estimation (MMAE) for discrete-time, linear, time-invariant MIMO plants with parameter uncertainty and unmodeled dynamics. Model identification is analyzed in a deterministic setting by adopting a Minimum Energy selection criterion. The MMAE system relies on a finite number of local observers, each designed using a selected model (SM) from the original set of possibly infinite plant models. Results akin to those previously obtained in a stochastic setting are derived in a far simpler manner, in a deterministic framework. We show, under suitable distinguishability conditions, that the SM identified is the one that corresponds to the observer with smallest output prediction error energy. We also develop a procedure to analyze the behavior of MMAE when the true plant is not one of the SMs. This leads to an algorithm that computes, for each SM, the set of equivalently identified plants, that is, the set of plants that will be identified as that particular SM. The impact of unmodeled dynamics on model identification is discussed. Simulation results with a model of a motor coupled to a load via an elastic shaft illustrate the performance of the methodology derived.

Cooperative Control of Multiple Marine Vehicles Theoretical Challenges and Practical Issues

Abstract This paper is a brief overview of some of the theoretical and practical issues that arise in the process of developing advanced motion control systems for cooperative multiple autonomous marine vehicles (AMVs). Many of the problems addressed have been formulated in the scope of the EU GREX project, entitled Coordination and Control of Cooperating Heterogeneous Unmanned Systems in Uncertain Environments. The paper offers a concise introduction to the general problem of cooperative motion control that is well rooted in illustrative mission scenarios developed collectively by the GREX partners. This is followed by the description of a general architecture for cooperative autonomous marine vehicle control in the presence of time-varying communication topologies and communication losses. The results of simulations with the NetMar SyS (Networked Marine Systems Simulator) of ISR/IST are presented and show the efficacy of the algorithms developed for cooperative motion control. The paper concludes with a description of representative results obtained during a series of tests at sea in the Azores, in 2008.

A general framework for multiple vehicle time-coordinated path following control

This paper describes a general framework for the study of multiple vehicle, time-coordinated path following (TC-PF) control problems. An example is the situation where a group of vehicles is tasked to maneuver and arrive at pre-assigned final positions at the same time in a collision-free manner, while reducing some optimality criterion. The time of arrival is not fixed a priori, and the vehicles must negotiate their speeds along the spatial paths that they follow in order to arrive simultaneously and avoid collision. The general framework adopted leads to integrated solutions to TC-PF problems that unfold in three steps: 1) Generation of Deconflicted Trajectories for a group of vehicles, 2) Path Following for each vehicle along its assigned path, and 3) Coordination of the relative motion of the vehicles along their paths, so as to guarantee deconfliction and meet desired temporal constraints such as equal times of arrival. The last step is accomplished by varying the speed of each vehicle about the nominal speed profile computed in step 1, based on the exchange of information with its neighbors. The paper formulates the problem mathematically, offers a general framework for its solution, and illustrates the efficacy of the proposed methodology in simulation with dynamic models of Autonomous Underwater Vehicles (AUVs).