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In recent years competition in the industrial world has become intense. As a result, the necessity for highly effective control techniques has increased. Furthermore, simple control structure and high robustness are also desirable. To meet these demands, model-driven type control theories type have been proposed. If these controllers are able to describe the model of the process accurately, then perfect...
Linearization is a standard part of modeling and control design theory for a class of nonlinear dynamical systems taught in basic undergraduate courses. Although linearization is a straight-line methodology, it is not applied correctly by many students since they often forget to keep the operating point in mind. This paper explains the topic and suggests a way to improve the teaching of the methodology...
This paper presents an extended Kalman filter for discrete-time nonlinear systems subject to uncertainties. The proposed filter considers that the linearization of the nonlinear functions are unknown, but within a known set. The nonlinear functions are assumed to belong to a conic region. This condition is characterized as a Lipschitz condition on the system state, control signal and the noise residuals...
In this paper, we deal with a class of nonholonomic driftless systems whose controllability Lie algebra is structurally different from that of chained form systems. We propose cross-chained systems as a class of these system. By extending the idea of Goursat's normal form used in the case of chained systems, we introduce a nilpotent normal form for cross-chained systems. We then give a necessary and...
This paper introduces a new hyperchaotic model, which is constructed based on a modified Chen system by introducing a dynamical controller. The system consists of four coupled first-order ordinary differential equations with three nonlinear cross-product terms and can generate a complex hyperchaotic attractor in a large parameter region. The basic dynamical properties of this hyperchaotic system are...
An algorithm based on extended Kalman filter applied to the sensorless PMSM drives to estimate rotor position and speed are described in this paper. The EKF is an optimal recursive estimation algorithm for estimating the states of dynamic nonlinear systems. The system simulation model is established in MATLAB/Simulink. And the sensorless PMSM drive system is implemented on the DSP employed field oriented...
A new type of global stability is introduced and its equivalent Lyapunov characterization is presented. The problem of global stability of the compact set composed by all invariant solutions of a nonlinear system (several equilibriums, for instance) is analyzed. Consideration of such set allows us to present global stability properties for multi-stable systems.
Port-based network modeling of complex physical systems naturally leads to port-Hamiltonian system models. This motivates the search for structure-preserving model reduction methods, which allow one to replace high-dimensional port-Hamiltonian system components by reduced-order ones. In this paper we treat a family of structure-preserving reduction methods for port-Hamiltonian systems, and discuss...
In this paper we present the integration of a linear-time-varying model-predictive-control (LTV-MPC), designed to stabilize a vehicle during sudden lane change or excessive speed-entry in curve, with a slip controller that converts the desired longitudinal tire force variation in pressure variation in the brake system. The lateral controller is designed using a three-degrees-of-freedom vehicle model...
In this paper, we extend the interconnection and damping assignment passivity-based control strategy to systems subjected to nonholonomic Pfaffian constraints. The results are applied to stabilize the pitch dynamics of an underactuated mobile inverted pendulum (MIP) robot subjected to nonholonomic constraints arising out of no-slip conditions. A novel feature of this paper is that we reduce the kinetic...
In this paper, we propose a new iterative learning control (ILC) scheme, which is devoted to dealing with unknown parameters that are both time varying and iteration varying. In particular, we consider iteration-varying parameters that are generated by a second-order internal model. By incorporating the internal model into the parametric learning law, the ILC scheme can handle more generic nonlinear...
The control of a new kind of airship is presented. By restricting its flight to a vertical plane, the mathematical model is reduced. The simplified model is proved to be minimum phase, and a nonlinear controller based on input-output linearization is designed. Since the performance of the controller is significantly impacted by the choice of parameters, simulations of three different pole placement...
Hula-hoop is not only one of familiar toys but also interesting system as a nonlinear control system. While humans play hula-hoop, hoop does not slide on the body but rotates around it. Though it is controlled only by the motion of the body, humans can realize enduring rotary motion without dropping hoop. The purpose of this paper is modeling and control of hula-hoop system as a nonlinear control...
We consider the multiplay model for hysteresis with nonlocal memory. This model consists of N mass/spring/dashpot with deadzone elements. The hysteresis map of the multiplay model is completely determined by the stiffness coefficients and widths of the gaps of the mass/spring/dashpot with deadzone elements. This multiplay model can be used to model a hysteretic system with a hysteresis map possessing...
In this paper we discuss and compare two methods to control the free gyroscope seeker scan loop system: centralized control structure and decentralized control structure. First a centralized controller based on the linear model of the seeker is provided. We next proceed to design a decentralized controller using a non-linear model of the seeker. Input-output pairing is a vital stage in decentralized...
This paper studies the global regulation problem for a class of nonlinear polynomial systems subject to both dynamic uncertainty and static uncertainty. The dynamic uncertainty does not vanish at the origin of the state space and thus is not input-to-state stable (ISS). As a result, the small gain theory based robust control technique alone cannot handle this problem. We manage to integrate both robust...
This paper addresses the exact transformation of nonlinear systems into a multiple model form with unmeasurable premise variables. The multiple model structure serves to treat the observability and the state estimation problem of nonlinear systems. Using a method with no information loss, a nonlinear system is transformed into a multiple model, depending on the choice of premise variables. It is a...
The paper studies how nonlinear PCH Hamiltonian systems are transformed under sampling. We show that Hamiltonian conservation can be preserved under sampling with respect to a modified output mapping. The impact of this result for computing sampled-data stabilizing controllers is illustrated on the basis of an example.
We consider a boundary feedback control problem for two coupled first-order hyperbolic partial differential equations with nonlinear coupling of Lotka-Volterra type. We use boundary control action on only one channel and design static and dynamic boundary controllers to drive the state at the end of the spatial domain to the desired constant reference values. The control design is based on a special...
In this work we focus on iterative learning control (ILC) design for tracking iteration-varying reference trajectories that are generated by high-order internal models (HOIM). An HOIM can be formulated as a polynomial operator between consecutive iterations to describe the changes of desired trajectories in the iteration domain. The classical ILC for tracking iteration-invariant reference trajectories,...
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