Rule Based Classifier Generation Using Symbiotic Evolutionary Algorithm

A new robust model predictive control (MPC) approach is proposed for constrained linear systems in this paper. It adopts a contractive state set as terminal set in MPC problem and employs a novel function of the state with respect to this terminal set as the stage cost of the objective function. When the controlled systems are subject to linear constraints, explicit MPC law can be obtained as a piecewise affine linear state feedback control law via multi-parameter linear programming method. The presented MPC, along with linear variable-structure control law associated with the terminal set, is essentially a dual mode control scheme to stabilize the constrained uncertain linear system. Compared to the existing MPC methods, the proposed approach have both better real-time applicability and more general robust stability guarantee.

The authors provide an alternative solution to the problem of semiglobal stabilization of a class of minimum phase nonlinear systems that was considered by A.R. Teel (1991). The method used yields a stabilizing linear state feedback law in contrast to a nonlinear state feedback law proposed by Teel. The peaking phenomenon is eliminated by inducing a specific time-scale structure in the linear part of the closed-loop system. This structure consists of a very slow and a very fast time scale. The crucial component in the method is the relation between the slow and the fast time-scales. The proposed linear state feedback control law has a single tunable gain parameter that allows for local asymptotic stability and regulation to the origin for any initial condition in some a priori given (arbitrarily large) bounded set. >

This paper presents a novel integral sliding mode control (ISMC) for singularly perturbed systems (SPSs) with matched disturbances. Firstly, a linear state feedback control law for the fast subsystem of SPS is designed, and the slow subsystem can be obtained. Secondly, an ISMC incorporating the disturbance estimate provided by a disturbance observer is designed. In order to attenuate matched disturbances, the Lyapunov function is employed to determine the gain of ISMC by solving a linear matrix inequality (LMI). As a result, the closed-loop slow subsystem under the ISMC is exponentially stable, and the full-order SPSs are exponentially stable under the composite control law. Finally, the effectiveness and advantages of the proposed method are demonstrated by simulations.

We provide an alternative solution to the problem of semi‐global stabilization of a class of minimum phase nonlinear systems which is considered in Reference 17. Our method yields a stabilizinglinearstate feedback law in contrast to anonlinearstate feedback law proposed in Reference 17. We eliminate the peaking phenomenon by inducing a specific time‐scale structure in the linear part of the closed‐loop system. This time‐scale structure consists of a very slow and a very fast time scale. The crucial component in our method is the relation between the slow and the fast time scales. Our proposed linear state feedback control law has asingletunable gain parameter that allows for local asymptotic stability and regulation to the origin for any initial condition in somea priorigiven (arbitrarily large) bounded set.

This paper is dealing with the receding horizon optimal control techniques having as main goal the reduction of the computational effort inherent to the use of on-line optimization routines. The off-line construction of the explicit solution for the associated multiparametric optimization problems is advocated with a special interest in the presence of nonlinearities in the constraints description. The proposed approach is a geometrical one, based on the topology of the feasible domain. The resulting piecewise linear state feedback control law has to accept a certain degree of suboptimality, as it is the case for local linearizations or decompositions over families of parametric functions. In the presented techniques, this is directly related to the distribution of the extreme points on the frontier of the feasible domain.

On interval observer design for active Fault Tolerant Control of Linear Parameter-Varying systems

In this paper, we develop an adaptive inverse compensation scheme for controlling the aerodynamic flow of a synthetic jet actuator on a dynamic aircraft system. An adaptive inverse is employed for cancelling the effect of the nonlinearity of the synthetic jet. A linear state feedback control law is used for controlling the aircraft dynamics. A linearly parametrized error model is derived for the nonlinear actuator model. A parameter projection adaptive law is used to ensure desired closed-loop stability and asymptotic tracking. An application of this adaptive compensation scheme to the control of a linear aircraft model with a synthetic jet actuator is studied and its effectiveness is verified by simulation results.

EXPLICIT HYBRID OPTIMAL CONTROLLER FOR DISTURBANCE ATTENUATION IN LINEAR HYBRID SYSTEMS

Preface. Chapter 1. Introduction. Chapter 2. State-Space Fundamentals. Chapter 3. Controllability. Chapter 4. Observability. Chapter 5. Minimal Realizations. Chapter 6. Stability. Chapter 7. Design of Linear State Feedback Control Laws. Chapter 8. Observers and Observer-Based Compensators. Chapter 9. Introduction To Optimal Control. References. Appendix A. Matrix Introduction. Appendix B. Linear Algebra. Appendix C. Continuing MATLAB Example m-File. References. Index.

Global Mittag–Leffler stabilization of fractional-order bidirectional associative memory neural networks

This chapter contains sections titled: State Feedback Control Law Shaping the Dynamic Response Closed-Loop Eigenvalue Placement via State Feedback Stabilizability Steady-State Tracking MATLAB for State Feedback Control Law Design Continuing Examples: Shaping Dynamic Response and Control Law Design Homework Exercises

Hopf bifurcations in normal forms of third order nonlinear affine control systems

Robust Stability of a linear, discrete-time, system with parturbations both in the system matrix and the input matrix of its state equation is considered. A robust linear state feedback control law is proposed to maximize the stable region defined in the perturbation space. Some extensions are outlined.

H∞ DISCRETE TIME FUZZY CONTROL WITH APPLICATION TO CHAOS CONTROL BASED ON PIECEWISE LYAPUNOV FUNCTIONS

Digital Control of Bilinear Continuous Processes. Application to a Chemical Pilot Plant.