Two-level Control Scheme Research Articles

Two-Level Nonlinear Model Predictive Control for Lean NOx Trap Regenerations

This paper describes a two-level nonlinear model predictive control (NMPC) scheme for diesel engine lean NOx trap (LNT) regeneration control. Based on the physical insights into the LNT operational characteristics, a two-level NMPC architecture with the higher-level for the regeneration timing control and the lower-level for the regeneration air to fuel ratio profile control is proposed. A physically based and experimentally validated nonlinear LNT dynamic model is employed to construct the NMPC control algorithms. The control objective is to minimize the fuel penalty induced by LNT regenerations while keeping the tailpipe NOx emissions below the regulations. Based on the physical insights into the LNT system dynamics, different choices of cost function were examined in terms of the impacts on fuel penalty and tailpipe NOx slip amount. The designed control system was evaluated on an experimentally validated vehicle simulator, cX-Emissions, with a 1.9 l diesel engine model through the FTP75 driving cycle. Compared with a conventional LNT control strategy, 31.9% of regeneration fuel penalty reduction was observed during a single regeneration. For the entire cold-start FTP75 test cycle, a 28.1% of tailpipe NOx reduction and 40.9% of fuel penalty reduction were achieved.

Two-level control strategy of an eight link biped walking model

This paper presents an adaptive two-level control strategy for a biped walking model and demonstrates its performance in a wide range of walking modes with considerably diverse model and control parameter settings. Proposed control strategy inherits a push off that resembles considerably to forceful extension of the trailing leg during push off in human locomotion and represents a very important source of forward propulsion. Extensive simulations have shown that adjustments in the push off related parameter on higher between-step control level after each step enable evolution of various walking modes of the biped walker at selected walking speeds and distinctive gait patterns. It also allows us to investigate the changes in gait kinematics and kinetics of the biped walking model due to changes in gait velocity, torso inclination and propulsion distribution profiles.

A two-level topology control strategy for energy efficiency in wireless sensor networks

This paper presents a two-level topology control strategy for energy efficiency in wireless sensor networks (WSNs). There are two types of energy saving approaches: active-subnetwork and transmission-range. The active-subnetwork approach increases the nodes' average sleeping time to save energy in a wireless sensor network, while the transmission-range approach reduces the energy consumption during packet delivery by adjusting the nodes' transmission ranges. By dynamically integrating the two approaches, our two-level approach achieves further energy saving. The simulation shows the performance advantage of our approach in different communication scenarios.

A two-level optimization based learning control strategy for wet clutches

This paper proposes a two-level control strategy for wet clutches. On the low level, the control signal is calculated by solving a constrained optimal control problem. On the high level, the measured responses are used to update the system models and constraints that are used in the optimization for the next control signal. In this way a learning algorithm is obtained, which is able to optimize the control signal during normal operation, despite its complex and time-varying dynamic behavior, and without requiring long calibrations or complex models. The performance and robustness of this control scheme are validated on an experimental test setup.

Constructing An Adaptive Color Reproduction System With Color Space Reference Regions Recognition

We discuss a problem of color reproduction upon printing. A two-level control scheme is proposed in which a problem of color space region recognition is first solved and then the current pixel's color coordinates are transformed into the basic inks’ concentration. At the preliminary stage, based on the spectra measured, the problem of model identification is solved for each region.

Human-like control strategy of a bipedal walking model

SUMMARYThis paper presents a two-level control strategy for bipedal walking mechanism that accounts for implicit control of push-off on the between-step control level and tracking of imposed holonomic constraints on kinematic variables via feedback control on within-step control level. The proposed control strategy was tested in a biologically inspired model with minimal set of segments that allows evolution of human-like push-off and power absorption. We investigated controller's stability characteristics by using Poincaré return map analysis in eight simulation cases and further evaluated the performance of the biped walking model in terms of how variations in torso position and gait velocity relate to push-off and power absorption. The results show that the proposed control strategy, with the same set of controller's gains, enables stable walking in a variety of chosen gait parameters and can accommodate to various trunk inclinations and gait velocities in a similar way as seen in humans.

A multi-form modelling approach to the dynamics and control of drum granulation processes

Drum granulation processes are represented by a set of mass transfer, solid transport, as well as population balance equations. The population balance is mathematically described by partial differential–integral equations. The overall granulation model is highly non-linear, large-scale with multiple coordinates and uncertain parameters, leading to tremendous difficulties for optimisation and control. In our previous work, a two-level control strategy is proposed, which consists of an upper level optimal control for the determination of optimal set-points, and a lower level non-linear model predictive control (NMPC) for the simultaneous computations of uncertain parameters and control variables. However, long computing times and insufficient measurement data prevent industrial applications. In this paper, strategies are developed to improve the applicability of the multi-level, model predictive control scheme (ML-MPC) using the multi-form modelling approach. In the multi-form modelling approach, the granulation plants are represented by a variety of model forms for different end-uses. These include: (1) the distributed parameter population balance model (DP-PBM), (2) the lumped parameter population balance model (LP-PBM), (3) matrix representation with off-line computed matrix elements, (4) local linear models, (5) reduced order models using balanced truncating and methods of moment. It can be shown through dynamic simulations that significant computing time reductions can be achieved with properly selected model forms. Since both open-loop optimal control and closed loop MPC rely on iterative dynamic optimisation, overall computing time reduction makes on-line applications possible. Furthermore, the development of local linear models allows the applications of well-established linear system theory and techniques to process control, parameter identification and model order reduction. The demonstrated advantages of the proposed multi-form modelling approach imply a big step forward towards the industrial applications of model-based control for granulation processes.

Parallel multi-model switched control for ship roll stabilization

This paper concerns the application of a parallel multi-model switched control (PMMSC) scheme for integrated fin and rudder roll stabilization (INFRRS). The PMMSC algorithm uses a two-level hierarchical control strategy where, at the lower level, a bank of controller pairs (fin roll and rudder roll controllers) are designed for a range of preselected operating conditions, and, at the upper level, a decision maker decides which controller pair is most suited to the prevailing conditions and ensures that the appropriate controller pair is switched into operation. A novel approach of characterizing roll angle data using power spectral density (PSD) histograms is presented. It is shown how the PSD histograms for different encounter angles exhibit sufficiently different characteristics to enable them to be used by the PMMSC algorithm to produce reliable switching between controller pairs. Simulation studies demonstrate the efficacy of the PMMSC when applied to an identified ship model.

FIAC: a resource discovery-based two-level admission control for differentiated service networks

Differentiated Service (DiffServ) architecture has been proposed as a scalable QoS architecture for Internet. DiffServ, however, could not control its loads under heavy traffic conditions, and it could not provide strong QoS responses for individual traffic flow. This paper introduces at the edges of a DiffServ domain, a novel two-level admission control scheme, the Fair Intelligent Admission Control (FIAC). At per-class level, FIAC admits traffic according their fairshare and usage while preventing possible congestion within the DiffServ core. At per-flow level, FIAC estimates and allocates the fairshare for each flow within a class. Simulation results demonstrate that FIAC adheres extremely well to the bandwidth requirements of DiffServ classes while preventing congestion within the DiffServ core. With FIAC's per-flow level enabled, FIAC is able to prevent uncontrolled UDP flows from depriving TCP-controlled flows of bandwidth share when they are aggregated to the DiffServ domain.

A Stdudy on ABS Slip Ratio Control of Vehicle using One Solenoid Valve

Anti-lock Braking System (ABS) is a safety device for preventing wheel-locking in a sudden braking. It consists of hydraulic modulator, ECU and wheel speed sensors. The hydraulic modulators are classified into two types; sot-flow type and sol-sol type. In this paper, the hydraulic modulator is composed of one solenoid valve with 3way-2position. The braking friction force described by function of slip ratio can obtained maximum value if slip ratio cartbe maintained from 0.1 to 0.3. Consequently, slip ratio is controlled by PWM and SMC based on vehicle dynamics in the same way a two-level control scheme.

Control of strip casting process: decentralization and optimal roll force control

In this paper, modeling and control of a twin-roll strip caster are investigated. The control objectives are to achieve a constant strip thickness and to maintain a constant roll separating force. Mathematical models are derived by analyzing five critical areas: molten steel level in the pool, solidification process, roll separating force and torque, roll gap dynamics, and roll drive dynamics. A two-level control strategy is proposed. At low level, three local controllers regulate three subsystems independently. They are a variable structure controller for the molten steel level of the pool, an adaptive predictive controller for the roll gap, which is directly related to the strip thickness, and a two-degree-of-freedom robust servo controller for the roll speed. At high level, an H2 optimal controller governs the interaction dynamics among subsystems and generates a reference signal to the local roll speed controller in the fashion that a constant roll separating force is maintained. In designing the high level controller, the complex strip casting dynamics is linearized at an operating point and parameter estimation and uncertainty quantification methods are used. Simulation results are provided. r 2001 Elsevier Science Ltd. All rights reserved.

An integrated system for supervision and economic optimal control of mineral processing plants

This work tackles the problem of dynamically optimising the performance of a mineral concentration plant, taking into account economic profits and technical constraints. The paper proposes a two-level control strategy with regulatory control and the optimisation of an objective function. The regulatory control employs linear model based multivariable predictive controllers with constraints on controlled and manipulated variables, while the optimiser maximises the economic profits using non-linear dynamic models and linear constraints. The results, drawn from simulations, show the proposed strategy to lead to a significant improvement in economic profits when compared against an exclusively regulatory strategy.

Decentralized Control of Two Cooperative Car-Like Robots Performing a Transportation Task

This paper describes an approach to the coordination of two car-like robots that must cooperate in accomplishing a transportation task, namely carrying a long beam that neither one can carry alone. The robots are not allowed any form of explicit exchange of information, and can therefore only "communicate" through the task that they perform together. We propose for this problem a decentralized controller that relies on a two-stage strategy. At the higher level, each robot computes, based on the information available to it, a desirable motion for the beam. The lower-level controller must then generate controls to be fed to the robot's actuators (its steering and propulsion motors), so that the beam's actual motion approximates as well as possible the desired one. This article presents our mathematical formalism and the derivation of the corresponding control laws. We present the results of simulation runs of this decentralized, two-level control strategy, as well as the experimental testbed built for studying such coordination tasks.

A Two-Level Hybrid Control for Bipedal Walking

In this paper a behaviour of two-legged walking mechanism with point foot-ground contact in the lateral plane was investigated. The model of a double inverted pendulum with only one actuator in the hip is used to represent dynamics of such a mechanism. For control synthesis of this underactuated mechanical system a hybrid approach is suggested: two-level control scheme with a fuzzy logic control at the first level and classical feedback-linearization based control at the second level. The classical control enables stabilization of a nominal trajectory from a predetermined set, while the fuzzy controller makes transition between nominal trajectories (phases of walking steps) and between appropriate classical controllerss. Nominal trajectory is determined by fuzzy-combination of several open-loop controllers for different state-space subsets. That controllers are synthesized by use of knowledge about the system behaviour, obtained by experimental measurements on real system and by computer simulations

The target mean problem for an arbitrary quality characteristic distribution

We consider the general problem of determination of an optimal process mean setting and the upper screening limit in relation to a fixed lower limit for a canning problem when the amount of fill follows an arbitrary continuous distribution. We show that the optimal upper limit is given by a very simple formula regardless of the shape of the distribution. We obtain a general condition to solve for the optimal process mean. Some specific distributions considered in the paper include normal, truncated normal, and truncated logistic. Comparisons are made in terms of the values of the optimal process mean, container rejection rate, and expected profit per fill attempt. Moreover, for any continuous fill distribution it is shown that a two-level control scheme with optimal upper limit is always economically superior to a single level scheme.

A two-level control strategy for robot manipulators

This paper deals with the hierarchical control of a class of robot manipulators. A two-level hierarchical control concept for robot manipulators is proposed. The controller is formulated based on a deterministic approach. In synthesizing the controller, it is assumed that the upper bounds on the nonlinearities, couplings and uncertainties present in the system are available. It is shown through computer simulations that the proposed control strategy is capable of withstanding the expected variations and uncertainties in the system, and will render the robot manipulator able to track a prescribed trajectory to within a small ultimate boundedness set.

Decentralized and Hierarchical Control of a Class of Robot Manipulators

This paper is concerned with the design of robust controllers for uncertain non-linear robot manipulators based on a deterministic approach. A decentralized tracking controller is presented in which the controller is designed for each subsystem based only on its local states. For the cases in which the interconnection functions between the subsystems are large, a two-level hierarchical control strategy is proposed. In designing the controllers, only the bounds on the system uncertainties are assumed to be known. It is shown theoretically and through computer simulations that the proposed controllers guarantee uniform ultimate boundedness of the error between the reference trajectory and the system output.

TWO-LEVEL OPTIMAL PI CONTROLLER DESIGN

ABSTRACT This paper addresses the design of two-level Power System Stabilizers using an optimal reduced order model whose state variables are torque angles and speeds. The reduced-order model retains their physical meaning and is used to design a two-level linear feedback controller that takes into account the realities and constraints of eletric power system. The two-level control strategy is used and a global control signal is generated from the output variables to minimize the effect of interactions. Effectiveness of this controller is evaluated and an example of a multimachine system, is given to illustrate the advantage of the proposed method. Reponses of the system with two-level scheme and optimal reduced order scheme are included for comparative analysis.

A Single-Chip Computer for Robust Variable-Structure Control of Large-Scale Safety-Critical Systems

Abstract This paper describes the specification and design of a low-cost advanced microcomputer controller suitable for use in large-scale process control systems in safety-critical applications. Accurate and robust decentralized control at a local level is achieved by a variable-structure controller with state observer. A suitable specification for a general-purpose microcontroller based on a RISC architecture is given, including the control procedure and its formal correctness proof. The proposed chip has fully integrated peripherals and may be connected via a network to a higher-level coordinating computer, permitting design, verification and downloading of control parameters. Interconnecting several microcontrollers, facilitates implementation of a two-level supervisory control strategy.

Two-level optimal output feedback stabilizer design

The paper addresses the design of two-level power system stabilizers using an optimal reduced order model whose state variables are torque angles and speeds. The reduced order model retains their physical meaning and is used to design a two-level linear feedback controller that takes into account the realities and constraints of electrical power systems. The two-level control strategy is used, and a global control signal is generated from the output variables to minimize the effect of interactions. The effectiveness of this controller is evaluated and a multimachine system is given as an example to illustrate the advantages of the proposed method. Responses of the system with a two-level scheme and an optimal reduced order scheme are included for comparative analysis.