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    ABSTRACT: A comparison is made between two vehicle control strategies for two different manoeuvres: a gentle and aggressive lane-change. Simulation results demonstrate that the choice of control objectives and selection of appropriate design approximations have a significant impact on the performance of the controller under these different manoeuvre conditions. A lateral control design trade-off between passenger comfort and collision avoidance capability is evident.
    Intelligent Vehicles Symposium, 2007 IEEE; 07/2007
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    ABSTRACT: The bond-graph method is a graphical approach to modeling in which component energy ports are connected by bonds that specify the transfer of energy between system components. Power, the rate of energy transport between components, is the universal currency of physical systems. Bond graphs are inherently energy based and thus related to other energy-based methods, including dissipative systems and port-Hamiltonians. This article has presented an introduction to bond graphs for control engineers. Although the notation can initially appear daunting, the bond graph method is firmly grounded in the familiar concepts of energy and power. The essential element to be grasped is that bonds represent power transactions between components
    IEEE control systems 05/2007;
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    ABSTRACT: The objective of this paper was to investigate whether a paraplegic subject is able to maintain balance during standing by means of voluntary and reflex activity of the upper body while being supported by closed loop controlled ankle stiffness using FES. The knees and hips of the subject were held in extended positions by a mechanical apparatus, which restricted movement to the sagittal plane. The subject underwent several training sessions where the appropriate level of stiffness around the ankles was maintained by the mechanical apparatus. This enabled the subject to learn how to use the upper body for balancing. After the subject gained adequate skills closed-loop FES was employed to regulate ankle stiffness, replacing the stiffness provided by the apparatus. A method to control antagonist muscle moment was implemented. In subsequent standing sessions, the subject had no difficulties in maintaining balance. When the FES support was withheld, the ability to balance was lost.
    IEEE Transactions on Neural Systems and Rehabilitation Engineering 01/2003; 10(4):239-48.
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    ABSTRACT: The paper starts with a brief history of the design of anti-lock brakes (ABS). The advantages of ABS are explained. For the analysis and controller design a nonlinear longitudinal car model is derived. It is shown that the dynamics can be separated conveniently into two different linear dynamics dependent on the tyre slip. The analysis of the dynamics show the highest possible braking performance. It is further shown that a continuous feedback law cannot not achieve the maximum braking performance. To achieve the maximum braking performance a sliding mode like controller design approach is suggested. The merits of this controller are shown in an example.
    American Control Conference, 2002. Proceedings of the 2002; 02/2002
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    ABSTRACT: This paper is concerned with the development and analysis of a nonlinear approach to modeling of the contraction of electrically stimulated skeletal muscle. The model structure is based on a network of locally valid linear models which are blended together by a scheduler. Data are from experiments with rabbit tibialis anterior muscles in which the muscles contracted isometrically while being stimulated by supramaximal impulses with randomly varying inter-pulse intervals. The model accounts for nonlinear effects due to variations of the stimulation frequency, such as the "catch-like" effect. It is shown that this modeling technique is suitable for modeling the contraction of muscles with very different characteristics, such as muscle with a majority of fast motor units and muscle with mainly slow motor units. The approach is also suitable as a basis for the design of muscle stimulation controllers. Index Terms-Functional electrical stimulation, local model network, muscle modeling, nonlinear system identification.
    IEEE Transactions on Biomedical Engineering 05/2001; 48(4):406-15.
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    ABSTRACT: This paper is concerned with the development and analysis of a nonlinear approach to modeling of the contraction of electrically stimulated skeletal muscle. The model structure is based on a network of locally valid linear models which are blended together by a scheduler. Data are from experiments with rabbit tibialis anterior muscles in which the muscles contracted isometrically while being stimulated by supra-maximal impulses with randomly varying inter-pulse intervals. The model accounts for nonlinear effects due to variations of the stimulation frequency, such as the "catch-like" effect. It is shown that this modeling technique is suitable fur modeling the contraction of muscles with very different characteristics, such as muscle with a majority of fast motor units and muscle with mainly slow motor units. The approach is also suitable as a basis for the design of muscle stimulation controllers.
    IEEE Transactions on Biomedical Engineering 01/2001; 48(4):406-415.
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    ABSTRACT: Implementation of model predictive control (MPC) or nonlinear systems requires the online solution of a nonconvex, constrained nonlinear optimisation problem. Computational delay and loss of optimality arise in the optimisation procedures. The paper presents a practical MPC scheme for nonlinear systems with guaranteed asymptotic stability. It is shown that when an initial control profile is chosen to satisfy an inequality condition in each online optimisation procedure, the nonlinear system under the proposed nonlinear MPC is asymptotically stable. The stability condition presented in the paper enables the `fictitious' terminal control to be nonlinear, rather than only linear, thus the stability region is greatly enlarged. Furthermore, it is pointed out that nominal stability is still guaranteed even though the global, or even the local, minimisation of the objective cost is not achieved within the prescribed computational time
    IEE Proceedings - Control Theory and Applications 08/2000;
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    ABSTRACT: A framework for the output tracking of nonlinear nonminimum phase systems is presented. The control problem is solved by a two degree of freedom design. A feedforward part generates an explicit trajectory for the nominal input and states by an analytic inversion of the plant to let the plant output follow an externally given reference trajectory. A gain scheduling controller stabilises the plant around these trajectories, the parameters of which are scheduled in dependence on the current nominal control signal and the nominal state vector. The design of the controller is based on a linear parameter varying model, which results from the linearisation of the plant about the nominal trajectories. An overview of techniques for the stable inversion of nonminimum phase systems is given. The approach is demonstrated on a bioreactor which shows maximum phase behaviour
    American Control Conference, 2000. Proceedings of the 2000; 02/2000
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    ABSTRACT: Simple, linear classical controllers are highly popular in industrial applications. However, most controllers have to be tuned and manually re-tuned on a trial and error basis at every operating level. This is particularly difficult when the plant to be controlled is significantly nonlinear. The deficiency in localised linearised models associated with `local model networks' has been overcome by the introduction of `linear approximation model (LAM) networks'. To address this problem and help in the design of industrial controllers for a wider range of operating trajectories,y, this paper develops a controller network design technique based upon a LAM network of a practical or nonlinear system to be controlled. This is called a `Trajectory Controller Network (TCN)', which overcomes the deficiency associated with local controller networks. Each element of a TCN can be of a simple form, such as PID, and may be obtained directly from a set of step response data at several typical operating levels for fast prototyping. Since plant step response data are often readily available in control engineering practice, such TCNs can be automatically and optimally evolved from these data directly without the need for model identification. The overall controller is co-ordinated and evolved along the entire operating trajectory in the operating envelope, tackling the control problem of practical or nonlinear plants. Evolutionary computation provides global structural search for the network and multi-objective optimisation of the controllers. This novel technique is illustrated and validated through a nonlinear control example
    Evolutionary Computation, 2000. Proceedings of the 2000 Congress on; 02/2000
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    ABSTRACT: A nonlinear disturbance observer for two link robotic manipulators is derived in the paper. The global exponential stability of the proposed disturbance observer is guaranteed by selecting design parameters which depend on the maximum velocity and the physical parameters of robotic manipulators. This observer overcomes the disadvantages of existing disturbance observers which are designed or analysed by linear system techniques. It can be applied in robotic manipulators for various purposes such as friction compensation, independent joint control, torque sensorless control and fault diagnosis. The performance of the proposed observer is demonstrated by friction estimation and compensation
    Decision and Control, 1999. Proceedings of the 38th IEEE Conference on; 02/1999
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