Showing papers in "Control Engineering Practice in 2012"

TL;DR: In this article, a nonlinear model predictive controller (MPC) and nonlinear disturbance observer is designed to estimate the influence of the external force/torque introduced by wind turbulences, unmodelled dynamics and variations of the helicopter dynamics.

TL;DR: Various recent developments in the area of nonlinear state estimators from a Bayesian perspective are reviewed, including the constrained state estimation, the handling of multi-rate and delayed measurements and recent advances in model parameter estimation.

TL;DR: In this article, a self-organizing radial basis function (RBF) neural network model predictive control (SORBF-MPC) method is proposed for controlling the dissolved oxygen (DO) concentration in activated sludge wastewater treatment processes (WWTPs).

TL;DR: In this article, the authors proposed a model predictive control scheme for real-time hybrid vehicle control, which requires the prediction of the future driving conditions and allows deriving a real time control strategy.

TL;DR: In this paper, a model predictive control (MPC) system is proposed to guide and control a chasing spacecraft during rendezvous with a passive target spacecraft in an elliptical or circular orbit, from the point of target detection all the way to capture.

TL;DR: In this paper, a nonlinear model predictive control (NMPC) strategy was proposed to manipulate the air flow rate in order to maintain the oxygen excess ratio in a desired value, both for safety and performance reasons.

TL;DR: In this paper, a robust discrete-time sliding mode control coupled with an uncertainty estimator designed for planar robotic manipulators is presented, where the tracking errors are proved, as well as boundedness of the estimation error with arbitrary precision.

TL;DR: In this article, two methods for recursive identification of Hammerstein systems are considered: the recursive least squares algorithm is applied to an over-parameterized representation of the Hammerstein model and a rank-1 approximation is used to recover the linear and nonlinear parameters from the estimated overparameterised form.

TL;DR: In this article, the use of FIR (Finite Impulse Response) filters for planning minimum-time trajectories for robots or automatic machines under constraints of velocity, acceleration, etc.

TL;DR: It is shown how the extra design freedom the point-to-point set-up brings allows additional input, output and state constraints to be simultaneously addressed, hence providing a powerful design framework of wide practical utility.

TL;DR: In this article, a multi-output least square support vector regressor is proposed, which considers not only the single fitting error of each tank level but also the combined one, and a particle swarm optimization is designed to determine the parameters of this model for the sake of improving the prediction accuracy.

TL;DR: In this paper, an adaptive model predictive control using an unscented Kalman filter (UKF) to estimate both the effective solar radiation and the metal-fluid temperature profiles is proposed.

TL;DR: This paper proposes a new approach for QoS performance management and resource provisioning by using an off-line identification of Hammerstein and Wiener nonlinear block structural model, using the characteristic structure of the nonlinear model to achieve the performance objectives.

TL;DR: In this paper, a robust model predictive controller (MPC) is used to solve the problem of spacecraft rendezvous, using the Hill-Clohessy-Wiltshire model with additive disturbances and line-of-sight constraints.

TL;DR: An integrated hardware and software design method is developed to implement an MPC algorithm on an FPGA chip, making it possible to achieve the long-desired goal of extending MPC algorithms to field control so as to deal with constraints effectively.

TL;DR: In this article, the authors apply the Virtual Reference Feedback Tuning (VRFT) to multiple-input multiple-output (MIMO) control strategies in wastewater treatment plants (WWTPs).

TL;DR: In this paper, the authors present a model predictive control approach for cycle-by-cycle control of HCCI while respecting constraints on actuators that might exist on a production implementation.

TL;DR: In this paper, a methodology is described to derive a reduced-order Linear Parameter Varying (LPV) model from a reference set of large-scale MIMO Linear Time Invariant (LTI) models describing a given system at frozen configurations.

TL;DR: In this article, a nonlinear dynamic model of a two-degrees-of-freedom manipulator containing all important terms is obtained and unknown parameters which are required to construct an LPV model are identified.

TL;DR: In this paper, a new synthesis method is presented to control air-fuel ratio (AFR) in spark ignition engines to maximize the fuel economy while minimizing exhaust emissions, where the time-varying delay in the control loop is first approximated by Pade approximation to render the system dynamics into non-minimum phase characteristics with time varying parameters.

TL;DR: In this article, a sensor-based observer, which resorts to rate gyro readings and a set of vector observations, estimates the bias of the estimated gyro bias and then estimates the attitude in the form of a rotation matrix.

TL;DR: New efficient algorithms are derived for this multi-order system identification with subspace-based identification algorithms and the closely related Eigensystem Realization Algorithm.

TL;DR: In this article, a unified motion controller for mobile manipulators is presented, which not only solves the problems of point stabilization and trajectory tracking but also the path following problem, and an adaptive controller for on-line updating the robot dynamics is also proposed.

TL;DR: In this article, the authors present some key operational challenges in the upstream petroleum industries in which advanced control and model-based optimization has or may have a significant impact, including stabilizing control on an individual well level, model based optimization for production allocation and long term recovery control.

TL;DR: In this article, the problem of modeling vehicle longitudinal motion is addressed for front wheel propelled vehicles, and a nonlinear controller is developed using the Lyapunov design technique and formally shown to meet its objectives i.e. perfect chassis and wheel speed regulation.

TL;DR: This paper examines the use of a so-called “generalised Hammerstein–Wiener” model structure that is formed as the concatenation of an arbitrary number of Hammerstein systems to be effective and, via Monte-Carlo simulation, relatively robust against capture in local minima.

TL;DR: In this article, a multi-mass-spring model is considered for the characterization of the most prominent sloshing modes, and a nonlinear mathematical model that reflects these specifications is derived.

TL;DR: In this paper, a multiple model based linear parameter varying (LPV) modeling scheme is proposed for handling nonlinearity in soft sensor development with irregular/missing output data, and the efficiency of the proposed algorithm is demonstrated through several numerical simulation examples as well as a pilot-scale experiment.

TL;DR: In this paper, a constrained output feedback model predictive control approach for nonlinear systems is presented, where the state variables are observed using an unscented Kalman filter, which offers some advantages over an extended Kalman Filter.

TL;DR: In this article, a sliding mode approach, called the three-mode control scheme, is incorporated into a two-channel bilateral teleoperation architecture, which can implement a position-position, force-force, or force-position scheme.