Conflicting Control Objectives Research Articles

Robust Control of Solid Oxide Fuel Cell Ultracapacitor Hybrid System

Mitigating fuel starvation and improving load-following capability of solid oxide fuel cells (SOFC) are conflicting control objectives. In this paper, we address this issue using a hybrid SOFC ultracapacitor configuration. Fuel starvation is prevented by regulating the fuel cell current using a steady-state invariant relationship involving fuel utilization, fuel flow, and current. Two comprehensive control strategies are developed. The first is a Lyapunov-based nonlinear control and the second is a standard H∞ robust control. Both strategies additionally control the state of charge of the ultracapacitor that provides transient power compensation. A hardware-in-the-loop test stand is developed where the proposed control strategies are verified.

Startup of a distillation column using intelligent control techniques

This work proposes the development of an intelligent predictive controller. Recurrent neural networks are used to identify the process, providing predictions about its behavior, based on control actions applied to the system. These information are then used by fuzzy controllers to accomplish a better control performance. Moreover, the fuzzy controller membership functions are evolved by Genetic algorithms (GA's) allowing an automatic tune of controllers. The combined use of these techniques make possible the control of multi-variable processes using several fuzzy controllers where the coupling among controlled variables are modeled by neural networks, and control objectives can be inserted into the GA fitness function. The methodology was applied to a simulation of the startup of a continuous distillation column. This process is chosen due to their characteristics, such as inertia, large accommodation time and conflicting control objectives that make these processes hard to control with traditional methods.

Nonlinear Backstepping Active Suspension Design Applied to a Half-Car Model

A fresh nonlinear backstepping design scheme, which is developed for the control of half-car active suspension systems to improve the inherent tradeoff between ride quality and suspension travel, is proposed in this paper. Since ride quality is dependent on a combination of vertical and angular displacements of a vehicle body, the design of active suspensions must have the potential to minimize heave and pitch movements in order to guarantee the ride comfort of passengers. The other important factor to be emphasized in the design of active suspensions is the suspension travel which means the space variation between the car body and the tires. In order to avoid damaging vehicle components and generating more passenger discomfort, the active suspension controllers must be capable of preventing the suspension from hitting its travel limits. Our design strategy, with two intentionally additional nonlinear filters, shows the potential to achieve these conflicting control objectives. The novelty of our active suspension design is in the use of two particular nonlinear filters at both the front and rear wheels. The effective bandwidths of these two nonlinear filters depend on the magnitudes of the front and rear suspension travels, individually. When suspension travel is small, the proposed controllers soften the suspension for enhancing passenger comfort. However, our control design shifts its attention to rattlespace utilization by stiffening the suspension when suspension travel approaches its limits. As a result, the improvement of tradeoff between ride quality and suspension travel can be guaranteed and is then demonstrated through comparative simulations.

Nonlinear backstepping control design of half-car active suspension systems

This paper develops a novel nonlinear backstepping design for the control of half-car active suspension systems to improve the inherent tradeoff between ride quality and suspension travel. Since ride quality depends on a combination of vertical displacement (heave) and angular displacement (pitch) of a vehicle body, an active suspension controller must be able to minimise heave and pitch movements in order to guarantee ride comfort of passengers. Suspension travel means the space variation between body and tire. To avoid damaging vehicle components and generating more passenger discomfort, the controller must be capable of preventing the suspension from hitting it travel limits. Our design with an additional nonlinear filter shows potentials to achieve these conflicting control objectives. The novelty is in the use of the nonlinear filter whose effective bandwidths depend on the magnitudes of linear combination of the front and rear suspension travels. This intentional introduction of nonlinearity, which is conveniently accommodated by backstepping, results in a design that is fundamentally different from previous active suspension designs. As the suspension travel changes, the nonlinear controller smoothly shifts its focus between the conflicting objectives of ride comfort and rattlespace utilisation. The suspension is set to be soft when suspension travel is small, and it is adjusted to become stiff as it approaches the travel limits. Therefore, this nonlinear design allows the closed-loop system to behave differently in different operating regions, thereby eliminating the dilemma of whether to use a soft or stiff suspension setting. As a result, the improvement of tradeoff between ride quality and suspension travel is demonstrated through comparative simulations.

COORDINATED FEEDBACK AND SWITCHING FOR WAVE SUPPRESSION

This work focuses on the problem of coordinating feedback and switching for the stabilization of the zero solution of the one-dimensional Kuramoto-Sivashinsky equation (KSE) with periodic boundary conditions and input constraints. Galerkin's method is initially used to derive a finite-dimensional system that captures the dominant dynamics of the KSE for a given value of the instability parameter. This ODE system is then used as the basis for the integrated synthesis, via Lyapunov techniques, of stabilizing nonlinear feedback controllers together with switching laws that orchestrate the switching between the admissible control actuator configurations, in a way that respects input constraints, accommodates inherently conflicting control objectives, and guarantees closed-loop stability. The theoretical results are successfully illustrated through computer simulations of the closed-loop system using a high-order discretization of the KSE.

Controller Tuning Based on Stochastic Control Theory

A practical controller tuning method is proposed for selecting controller gains in the face of design difficulties such as poor repeatability, long delay, nonlinearity, conflicting control objectives, model inaccuracy, and system complexity. Unlike many adaptive schemes striving to acquire knowledge about the system being controlled, the proposed approach is aimed at designing nonadaptive, or at best, gain scheduling controllers in a quantitative, systematic way while meeting design specifications.