Photogrammetry is a well-studied and much-used analysis tool. Typical use cases include area surveillance, flood monitoring and related tasks. Usually, an Unmanned Aerial System (UAS) is used as support for image acquisition from an a priori delimited region in a semi-automated manner (via a mix of ground control and autonomous trajectory tracking). This in turn has led to various algorithms which
handle path trajectory generation under realistic constraints but still many avenues remain open. In this paper, we consider typical costs and constraints (UAS dynamics, total-path length, line inter-distance, turn points, etc.) in order to obtain, via optimization procedures, an optimal trajectory. To this end we make use of polyhedral set operations, flat trajectory generation and other similar tools. Additional work includes the study of non-convex regions and estimation of the number of photographs taken via Ehrhart polynomial computations.
Present article provides a set-based fault tolerant control strategy for multi-sensor systems, where sensors are communicating with a controller via a shared network. Possible faults, such as abrupt sensor outages and network-induced delays, are identified as degradation modes which might affect the information provided by each sensor. Measurements that are transmitted from a sensor to the controller are characterized by a residual signal which is sensitive to the sensor's abrupt faults and network-induced delays. In order to avoid control based on information which is provided by a faulty sensor, we designed a fault detection and isolation mechanism that is implemented through a set membership evaluation. This evaluation differentiates between ``healthy'', ``faulty'' and ``delayed'' data transmission. Unequivocal fault detection and isolation are assured if the corresponding sets are disjoint. Since in general this is not the case, sets separation is enforced by a reference governor. Fault detection and isolation mechanism is design in order to transmit only measurements from sensors which are fully operational, even if potentially affected by delays. If there is a delayed information that reaches the controller, then control action is reconfigured in order to govern the plant as close as possible to the reference signal. Such control action is provided by a model-based controller with compensation block. Sufficient condition that guarantees the existence of the compensation signal is presented as well.
This paper presents an extension of a MPC (Model Predictive Control) approach for microgrid energy management which takes into account electricity costs, power consumption, generation profiles, power
and energy constraints as well as uncertainty due to variations in the environment. The approach is based on a coherent framework of control tools, like mixed-integer programming and soft constrained
MPC, for describing the microgrid components dynamics and the overall system control architecture Fault tolerant strategies are inserted in order to ensure the proper amount of energy in the storage
devices such that (together with the utility grid) the essential consumer demand is always covered. Simulation results on a particular microgrid architecture validate the proposed approach.
In this paper, we consider a multi-sensor networked control configuration with linear plant which is affected by a bounded additive disturbance. Shared network is used for the communication between sensors and controller. It is assumed that the sensors are prone to abrupt faults, while the controller’s input may be updated with a varying time-delay. In order to identify and isolate the sensor(s) providing faulty information, we
equip the controller with a set-based detection and isolation routine. Furthermore, in the case when the network induces time-delays, control is performed based on the knowledge we have on the mathematical model
of the plant. In the presence of model inaccuracies or disturbance, such a control action may not guarantee satisfying performance of the system. Therefore, a stabilising controller with delay compensation has
been designed. The functioning of the proposed control algorithm has been illustrated through an example.
In this paper, an actuator-fault detection and isolation (FDI) approach is proposed. The FDI approach is based on a bank of interval observers, each of which is designed to match a healthy or faulty system mode. To ensure reliable FDI for all considered actuator faults, a collection of invariant set-based FDI conditions are established for the proposed technique. Under these guaranteed FDI conditions, all the considered faults can be detected and isolated during the transition induced by fault occurrences. Comparing with the existing set-based FDI approaches, the advantage of the proposed technique consists in that it combines the advantages of interval observers in the transient-state functioning and the advantages of invariant sets in the steady-state functioning. This paper is completed with the study of a continuous stirred-tank reactor (CSTR), which illustrates the effectiveness of the proposed method.
The present paper proposes a switching control scheme for a plant with multiple sensor–estimator/control–actuator pairs. The scheme is shown to handle the specific stability problems originated by the switching between the different feedback loops and accommodate to faults in the measurement (sensors) channels. The main contribution is a fault tolerant switching scheme with stability guarantees assured by a pre-imposed dwell time. The detection and the fault tolerance capabilities are achieved through the separation of sets associated with suitable residual signals corresponding to healthy and faulty functioning. Another contribution of the paper resides in a recovery technique for the post-fault reintegration of the biased estimations. This technique makes use of a virtual sensor whose associated estimation, based on an optimization procedure, minimizes the recovery time.
Soft constraints and penalty functions are commonly used in MPC to ensure that the optimization problem has a feasible solution, and thereby avoid MPC controller failure. On the other hand, soft constraints may allow for unnecessary violations of the original constraints, i.e., the constraints may be violated even if a valid solution that does not violate any constraints exists.
The paper develops procedures for the minimizing (according to some norm) of the Lagrange multipliers associated with a given mp-QP problem, assumed to originate from an MPC problem formulation. To this end the LICQ condition is exploited in order to efficiently formulate the optimization problem, and thereby improve upon existing mixed integer formulations and enhance the tractability of the problem. The results are used to design penalty functions such that corresponding soft constraints are made exact, that is, the original (hard) constraints are violated only if there exists no solution where all constraints are satisfied.
The present paper deals with the interplay between healthy and faulty sensor functioning in a multisensor scheme based on a switching control strategy. Fault tolerance guarantees have been recently obtained in this framework based upon the characterisation of invariant sets for state estimations in healthy and faulty functioning. A source of conservativeness of this approach is related to the issue of sensor recovery. A common working hypothesis has been to assume that once a sensor switches to faulty functioning it can no longer be used by the control mechanism even if at an ulterior moment it switches back to healthy functioning. In the current paper, we present necessary and sufficient conditions for the acknowledgement of sensor recovery and we propose and compare different techniques for the reintegration of sensors in the closed-loop decision-making mechanism.
This paper is concerned with improvements in constraints handling for mixed-integer optimization problems. The novel element is the reduction of the number of binary variables used for expressing the complement of a convex (polytopic) region. As a generalization, the problem of representing the complement of a possibly not connected union of such convex sets is detailed. In order to illustrate the benefits of the proposed improvements, a typical control application, the control of multiagent systems using receding horizon optimization techniques, is considered.
The present paper deals with the reference tracking problem for processes with linear dynamics and multisensor information subject to abrupt sensor faults. A key point for fault tolerance will be the separation between healthy and faulty closed-loop behavior upon a set-characterization approach. This is achieved through set theoretic operations involving the healthy/faulty behavior of residual signals related to the system dynamics. As a main contribution, a reference governor scheme is designed using a receding horizon technique. It is shown that fault detection guarantees can be achieved by appropriate adjusting of the governor's delay/prediction window under mild assumptions on the fault scenario.
In this study, set theoretic methods are used to design a fault-tolerant scheme for a multisensor control application. The basic principle is the separation of the invariant sets for the estimations of the state and tracking error under healthy and faulty functioning. The fault scenario assumes abrupt changes of the observation equations. The main contribution of this paper is the introduction of controlled invariant sets in the fault detection mechanism. The control action is chosen in order to guarantee the closed-loop positive invariance of a candidate region when the exogenous signals (additive disturbances, noise and reference/set-points) are bounded.
This article deals with fault tolerant multisensor control schemes for systems with linear dynamics. Positive invariance is a common analysis and control design tool for systems affected by bounded constraints and disturbances. This article revisits the construction of \epsilon-approximations of minimal robust positive invariant sets
for linear systems upon contractive set-iterations. The cases of switching between different sets of disturbances and the inclusion of a predefined region of the state space are treated in detail. All these results are used in multisensor control schemes which have to deal with specific problems originated by the switching between different estimators and by the presence of faults in some of the sensors. The construction of positive invariant sets for different operating regimes provides, in this context, effective fault detection information. Within the same framework, global stability of the switching strategies can be assured if the invariant sets topology allows
the exclusive selection of estimates obtained from healthy sensors.