Showing papers presented at "American Control Conference in 2014"

Distributed PI-control with applications to power systems frequency control

Abstract: This paper considers a distributed PI-controller for networked dynamical systems. Sufficient conditions for when the controller is able to stabilize a general linear system and eliminate static control errors are presented. The proposed controller is applied to frequency control of power transmission systems. Sufficient stability criteria are derived, and it is shown that the controller parameters can always be chosen so that the frequencies in the closed loop converge to nominal operational frequency. We show that the load sharing property of the generators is maintained, i.e., the input power of the generators is proportional to a controller parameter. The controller is evaluated by simulation on the IEEE 30 bus test network, where its effectiveness is demonstrated.

Security of smart distribution grids: Data integrity attacks on integrated volt/VAR control and countermeasures

Abstract: We examine the feasibility of an attack on themeasurements that will be used by integrated volt-var control(VVC) in future smart power distribution systems. The analysisis performed under a variety ...

Nested Saturation Control of an UAV carrying a suspended load.

Abstract: This paper addresses the problem of using unmanned aerial vehicles for the transportation of suspended loads. The proposed solution introduces a novel control law capable of steering the aerial robot to a desired reference while simultaneously limiting the sway of the payload. The stability of the equilibrium is proven rigorously through the application of the nested saturation formalism. Numerical simulations demonstrating the effectiveness of the controller are provided.

Model based active power control of a wind turbine

Abstract: In recent decades there has been increasing interest in green energies, of which wind energy is one of the most important. Wind turbines are the most common wind energy conversion systems and are hoped to be able to compete with traditional power plants in near future. This demands better technology to increase competitiveness of the wind power plants. One way to increase competitiveness of wind power plants is to offer grid services (also called ancillary services) that are normally offered by traditional power plants. One of the ancillary services is called reserve power. There are instants in the electricity market that selling the reserve power is more profitable than producing with the full capacity. Therefore wind turbines can be down-regulated and sell the differential capacity as the reserve power. In this paper we suggest a model based approach to control wind turbines for active power reference tracking. We use model predictive control (MPC) as our control method. We compare three different control strategies, namely Max-Ω, Constant-Ω and Constant-λ and discuss their drawbacks and benefits by presenting analysis of the steady state operating points and simulations on a high fidelity wind turbine model.

MPC design for rapid pump-attenuation and expedited hyperglycemia response to treat T1DM with an Artificial Pancreas

Abstract: The design of a Model Predictive Control (MPC) strategy for the closed-loop operation of an Artificial Pancreas (AP) for treating Type 1 Diabetes Mellitus (T1DM) is considered in this paper. The contribution of this paper is to propose two changes to the usual structure of the MPC problems typically considered for control of an AP. The first proposed change is to replace the symmetric, quadratic input cost function with an asymmetric, quadratic function, allowing negative control inputs to be penalized less than positive ones. This facilitates rapid pump-suspensions in response to predicted hypoglycemia, while simultaneously permitting the design of a conservative response to hyperglycemia. The second proposed change is to penalize the velocity of the predicted glucose level, where this velocity penalty is based on a cost function that is again asymmetric, but additionally state-dependent. This facilitates the accelerated response to acute, persistent hyperglycemic events, e.g., as induced by unannounced meals. The novel functionality is demonstrated by numerical examples, and the efficacy of the proposed MPC strategy verified using the University of Padova/Virginia metabolic simulator.

Active fault detection in MIMO systems

Abstract: The focus in this paper is on active fault detection (AFD) for MIMO systems with parametric faults. The problem of design of auxiliary inputs with respect to detection of parametric faults is investigated. An analysis of the design of auxiliary inputs is given based on analytic transfer functions from auxiliary input to residual outputs. The analysis is based on a singular value decomposition of these transfer functions Based on this analysis, it is possible to design auxiliary input as well as design of the associated residual vector with respect to every single parametric fault in the system such that it is possible to detect these faults.

Fixed step clutch modeling and simulation for automotive real-time applications

Abstract: Efficient coordination of actuating elements is an important challenge for modern automotive control units in order to deliver the requested torque for propulsion during all driving conditions. Model-based approaches have large potential to deal with the growing complexity. The need for real-time execution leads to fixed time step solution of the model equations. Solving model equations containing friction elements is a major challenge, since adaptive time step methods involving zero crossing detection are not feasible for real-time execution. This publication focuses on a technique for modeling complex drivetrain layouts that contain several friction elements like clutches and brakes. The main target of this contribution is to loosen requirements on maximum time step size which arise due to discontinuous friction modeling within the model equations. The proposed approach enables model-based calculations at larger time step sizes. This permits online calculation of complex gear transmission models at usual time rasters of common automotive control units.

Output-feedback global tracking control of robot manipulators with flexible joints

Abstract: We present a controller for flexible-joint robots without link velocity measurement. Our main result consists in a simple controller of the type proportional-derivative plus feedforward and a series of cascaded filters; the control design is reminiscent of classical backstepping control. To avoid the assumption that link velocities, accelerations and jerks are measured, we use approximate differentiation. The originality of our work lays in establishing uniform global asymptotic stability for the closed-loop system.

Abstractions and Sensor Design in Partial-information, Reactive Controller Synthesis

Abstract: Automated synthesis of reactive control protocols from temporal logic specifications has recently attracted considerable attention in various applications, for example, robotic motion planning, network management, etc. An implicit and often unrealistic assumption in this past work is the availability of complete and precise sensing information during the execution of the controllers. In this paper, we use an abstraction procedure for systems with partial observation and propose a formalism to investigate the effects of limitations in sensing. The abstraction procedure enables the existing synthesis methods with partial observation to be applicable and efficient for systems with infinite (or finite but large number of) states. This formalism enables us to systematically discover necessary sensing modalities for rendering the underlying synthesis problems realizable. We use counterexamples, which witness unrealizability potentially due to the limitations in sensing and the coarseness of the abstraction, and interpolation-based techniques to refine the model and the sensing modalities, i.e., to identify new sensors to be included, for the control objective. We demonstrate the method on robot motion planning examples.

Controller modification applied for active fault detection

Abstract: This paper is focusing on active fault detection (AFD) for parametric faults in closed-loop systems. This auxiliary input applied for the fault detection will also disturb the external output and consequently reduce the performance of the controller. Therefore, only small auxiliary inputs are used with the result that the detection and isolation time can be long. In this paper it will be shown, that this problem can be handled by using a modification of the feedback controller. By applying the YJBK-parameterization (after Youla, Jabr, Bongiorno and Kucera) for the controller, it is possible to modify the feedback controller with a minor effect on the external output in the fault free case. Further, in the faulty case, the signature of the auxiliary input can be optimized. This is obtained by using a band-pass filter for the YJBK parameter that is only effective in a small frequency range where the frequency for the auxiliary input is selected. This gives that it is possible to apply an auxiliary input with a reduced amplitude. An example is included to show the results. Keyword: Active fault detection, parametric faults, feedback controllers, YJBK parameterization, controller modification. I. INTRODUCTION The area of fault diagnosis (FD) includes various methods based on passive observation of the systems and methods based on active excitation of the systems.

Estimation of Linear Parameter-Varying affine state space models using synchronized periodic input and scheduling signals

Abstract: During the past decades some very interesting results have been obtained in controller synthesis using Linear Parameter-Varying (LPV) systems. However, the LPV models are commonly required to be transformed into State Space (SS) form. We tackle the LPV SS identification problem directly in the frequency domain. To the best of our knowledge, this is a novel approach. When the input and scheduling are chosen to be periodic and synchronized, the state space equations are structured and sparse in the frequency domain. The parameters of these state space equations are estimated by minimizing a weighted non-linear least squares criterion. Starting values are generated via the Best Linear Time-Invariant (BLTI) approximation. The resulting model is also valid for non-periodic scheduling and input signals.

Unscented statistical linearization and robustified Kalman filter for nonlinear systems with parameter uncertainties

Abstract: Kalman filter (KF) design is well established for perfectly known linear system and observation models. Real-world phenomena, however, have significant associated uncertainties, and the tuning of the KF is not so straightforward for tackling them. In this paper, we present a method of designing a robust filter for nonlinear systems with model parameter uncertainties. The uncertainties are imposed on the temporal changes in system parameters, which corresponds to the conditions that most real-world problems exhibit. Our proposed filter is based on a robustified KF, which assumes Gaussian distributed states and is designed to be robust to significant changes in the system parameters. The uncertain nonlinear systems are handled by using the linearized approximation models to guarantee the Gaussianity of states. This is achieved by using a statistical linearization in conjunction with unscented transformations and we thus call the linearization technique unscented statistical linearization (USL). The USL is employed for the prediction step of nonlinearly transformed state and the subsequent filtering is executed by using the robustified KF to make the filter robust to upcoming observations. We call our proposed filter for the uncertain nonlinear systems a robustified nonlinear KF (robustified NKF) and confirm the effectiveness by experiments using artificially generated data.

A feedback linearization controller for trajectory tracking of the Furuta pendulum

Abstract: A Furuta pendulum is a two degrees-of-freedom mechanism consisting of an arm rotating in the horizontal plane and a pendulum rotating in the vertical plane. The pendulum is attached to the arm tip. The complexity in the control of this system relies on that only the arm is actuated. The problem addressed in this paper consists in the design of a controller such that the difference between the desired joint position and the actual one is uniformly ultimately bounded. In particular, the desired arm position is a time varying signal and the desired pendulum position is zero. Roughly speaking, this has the physical meaning that the arm should be moving while the pendulum should be kept at the upward position. To satisfy that control goal, in this document a new controller based on the feedback linearization technique is introduced. The new scheme has been experimentally compared with respect to a known algorithm.

Reconfigurable Fault Tolerant Control for nonlinear aircraft based on concurrent SMC-NN adaptor

Abstract: This work focuses on an improved reconfigurable Fault Tolerant Flight Control (FTFC) strategy based on a traditional model reference Neural Network (NN) adaptive flight control architecture. An expanded control scheme is developed by using a concurrent learning NN strategy combined with the Sliding Mode Control (SMC) theory. The improved NN using concurrent update information to compensate for model inversion error is described for the full dynamic characteristics of the aircraft system. The SMC is implemented to treat the NN as a controlled system and allows a stable, dynamic calculation of the learning rates. The proposed reconfigurable FTFC system based on concurrent SMC-NN adaptor is tested on a nonlinear Unmanned Aerial Vehicle (UAV), the Machan UAV, in the presence of fault and disturbance scenarios. The results show that the designed controller achieves better adaptive performance by using the SMC in on-line concurrent NN learning law.

Backstepping control of PDEs with time-varying domain

Abstract: In this work a PDE backstepping-based control law for one-dimensional unstable heat equation with time-varying spatial domain is developed. The underlying parabolic partial differential equation (PDE) with time-varying domain is the model emerging from process control applications such as crystal growth. In backstepping control law synthesis, a characteristic feature is that the PDE describing the transformation kernel of the associated Volterra integral is time-dependent. In this work, the kernel PDE is solved numerically and the state-feedback controller is simulated for the application of temperature regulation in the Czochralski crystal growth process.

A robust observer for switched-reluctance motors

Abstract: We present a simple state observer for switched reluctance motors using stator currents. The estimation error dynamics is showed to be input-to-state stable with respect to (current, velocity and angular position) tracking errors as well as relative to load-torque compensation mismatch. The state estimator is designed in the context of the certainty-equivalence principle and proportional-integral-derivative control.

On experimentally validated iterative learning control in human motor systems

Abstract: A framework is developed to construct computational models of the human motor system (HMS) using various iterative learning control (ILC) update structures. Optimal models of movement are introduced using a general cost function (involving both tracking objective and an additional constraint term), and its parameters are fitted to observed limiting solutions corresponding to learned human motion obtained from experiments. Three general ILC update structures are considered which each generate the required limiting solution using different forms of experimental data. It is shown how the parameters in each which govern convergence may also be fitted to experimental learning data, with the different ILC structures permitting varying degrees of freedom in capturing the observed learning transients. Experimental results in which a participant uses a planar robot to perform reaching tasks confirm the ability of the proposed ILC structures to accurately model the learning ability of the human motor system.

Control laboratory experiments in thermoacoustics using the Rijke tube

Abstract: We report on experiments that investigate the dynamics, identification and control of thermoacoustic phenomena in a Rijke tube apparatus. These experiments are relatively simple to construct and conduct in a typical, well-equipped undergraduate controls laboratory, yet allow for the exploration of rich and coupled acoustic and thermal dynamics, the associated thermoacoustic instabilities, and the use of acoustic feedback control for their stabilization. We describe the apparatus construction, investigation of thermoacoustic dynamics and instabilities in both open-loop and closed-loop configurations, closed-loop identification of the underlying dynamics, as well as model validation. We also summarize a transcendental transfer function analysis that explains the underlying phenomena. These experiments are notable for the fact that rich thermoacoustic phenomena can be analyzed using introductory concepts such as the frequency response and root locus, and thus can be performed and understood by controls students with relatively little background in acoustics or heat transfer.

Path Tracking with Obstacle Avoidance for Pseudo-Omnidirectional Mobile Robots Using Convex Optimization

Abstract: We consider time-optimal path tracking for the class of pseudo-omnidirectional mobile robots. An Euler- Lagrange model of the robot dynamics is derived, and by writing it on special form a convex reformulation of the path-tracking problem can be utilized. This enables the use and regeneration of time-optimal trajectories during runtime. The proposed approach also incorporates avoidance of moving obstacles, which are unknown a priori. Using sensor data, objects along the desired path are detected. Subsequently, a new path is planned and the corresponding time-optimal trajectory for tracking of the generated path is found. The robustness of the method and its sensitivity to model errors are analyzed and discussed with extensive simulation results. Moreover, we verify the approach by successful execution on a physical setup. I. INTRODUCTION

Failure Boundary Estimation for lateral collision avoidance manoeuvres

Abstract: This paper proposes a method for predicting the point at which a simple lateral collision avoidance manoeuvre fails. It starts by defining the kinematic failure boundary for a range of conflict geometries and velocities. This relies on the assumption that the ownship aircraft is able to turn instantaneously. The dynamics of the ownship aircraft are then introduced in the form of a constant rate turn model. With knowledge of the kinematic boundary, two optimisation algorithms are used to estimate the location of the real failure boundary. A higher fidelity simulation environment is used to compare the boundary predictions. The shape of the failure boundary is found to be heavily connected to the kinematic boundary prediction. Some encounters where the ownship aircraft is travelling slower than the intruder were found to have large failure boundaries. The optimisation method is shown to perform well, and with alterations to the turn model, its accuracy can be improved. The paper finishes by demonstrating how the failure boundary is used to determine accurate collision avoidance logic. This is expected to significantly reduce the size and complexity of the verification problem.