55 research outputs found

    Virtual actuators with virtual sensors

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    The virtual actuator approach to bond graph based control is extended to use virtual sensor inputs; this allows relative degree conditions on the controller to be relaxed. Furthermore, the effect of the transfer system can be eliminated from the closed loop system. Illustrative examples are given

    Estimation of the parameters of continuous-time systems using data compression

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    This chapter provides a unified introductory account of the estimation of the parameters of continuous-time systems using data compression based on a number of previous publication

    Predictive pole-placement control with linear models

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    The predictive pole-placement control method introduced in this paper embeds the classical pole-placement state feedback design into a quadratic optimisation-based model-predictive formulation. This provides an alternative to model-predictive controllers which are based on linear–quadratic control. The theoretical properties of the controller in a linear continuous-time setting are presented and a number of illustrative examples are given. These results provide the foundation for novel linear and nonlinear constrained predictive control methods based on continuous-time models

    A nonlinear disturbance observer for robotic manipulators

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    A new nonlinear disturbance observer (NDO) for robotic manipulators is derived in this paper. The global exponential stability of the proposed disturbance observer (DO) is guaranteed by selecting design parameters, which depend on the maximum velocity and physical parameters of robotic manipulators. This new observer overcomes the disadvantages of existing DOs, which are designed or analyzed by linear system techniques. It can be applied in robotic manipulators for various purposes such as friction compensation, independent joint control, sensorless torque control and fault diagnosis. The performance of the proposed observer is demonstrated by the friction estimation and compensation for a two-link robotic manipulator. Both simulation and experimental results show the NDO works well

    Causality in real-time dynamic substructure testing

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    Causality, in the bond graph sense, is shown to provide a conceptual framework for the design of real-time dynamic substructure testing experiments. In particular, known stability problems with split-inertia substructured systems are reinterpreted as causality issues within the new conceptual framework. As an example, causality analysis is used to provide a practical solution to a split-inertia substructuring problem and the solution is experimentally verified

    Bond graph based control and substructuring

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    A bond graph framework giving a unified treatment of both physical-model based control and hybrid experimental–numerical simulation (also known as real-time dynamic substructuring) is presented. The framework consists of two subsystems, one physical and one numerical, connected by a transfer system representing non-ideal actuators and sensors. Within this context, a two-stage design procedure is proposed: firstly, design and/or analysis of the numerical and physical subsystem interconnection as if the transfer system were not present; and secondly removal of as much as possible of the transfer system dynamics while having regard for the stability margins established in the first stage. The approach allows the use of engineering insight backed up by well-established control theory; a number of possibilities for each stage are given. The approach is illustrated using two laboratory systems: an experimental mass-spring-damper substructured system and swing up and hold control of an inverted pendulum. Experimental results are provided in the latter case

    Bond graphs in model matching control

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    Bond graphs are primarily used in the network modeling of lumped parameter physical systems, but controller design with this graphical technique is relatively unexplored. It is shown that bond graphs can be used as a tool for certain model matching control designs. Some basic facts on the nonlinear model matching problem are recalled. The model matching problem is then associated with a particular disturbance decoupling problem, and it is demonstrated that bicausal assignment methods for bond graphs can be applied to solve the disturbance decoupling problem as to meet the model matching objective. The adopted bond graph approach is presented through a detailed example, which shows that the obtained controller induces port-Hamiltonian error dynamics. As a result, the closed loop system has an associated standard bond graph representation, thereby rendering energy shaping and damping injection possible from within a graphical context

    An adaptive polynomial based forward prediction algorithm for multi-actuator real-time dynamic substructuring

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    Real-time dynamic substructuring is a novel experimental technique used to test the dynamic behaviour of complex structures. The technique involves creating a hybrid model of the entire structure by combining an experimental test piece—the substructure—with a set of numerical models. In this paper we describe a multi-actuator substructured system of a coupled three mass–spring–damper system and use this to demonstrate the nature of delay errors which can first lead to a loss of accuracy and then to instability of the substructuring algorithm. Synchronization theory and delay compensation are used to show how the delay errors, present in the transfer systems, can be minimized by online forward prediction. This new algorithm uses a more generic approach than the single step algorithms applied to substructuring thus far, giving considerable advantages in terms of flexibility and accuracy. The basic algorithm is then extended by closing the control loop resulting in an error driven adaptive feedback controller which can operate with no prior knowledge of the plant dynamics. The adaptive algorithm is then used to perform a real substructuring test using experimentally measured forces to deliver a stable substructuring algorithm

    Bond graph modelling of chemoelectrical energy transduction

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    Energy-based bond graph modelling of biomolecular systems is extended to include chemoelectrical transduction thus enabling integrated thermodynamically-compliant modelling of chemoelectrical systems in general and excitable membranes in particular. Our general approach is illustrated by recreating a well-known model of an excitable membrane. This model is used to investigate the energy consumed during a membrane action potential thus contributing to the current debate on the trade-off between the speed of an action potential event and energy consumption. The influx of Na+ is often taken as a proxy for energy consumption; in contrast, this paper presents an energy based model of action potentials. As the energy based approach avoids the assumptions underlying the proxy approach it can be directly used to compute energy consumption in both healthy and diseased neurons. These results are illustrated by comparing the energy consumption of healthy and degenerative retinal ganglion cells using both simulated and in vitro data

    Intermittent predictive control

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    It is shown that the concept of intermittent control, to be found in the physiological literature, provides a useful alternative to both continuous-time and discrete-time approaches to control system design. In particular an intermittent version of predictive pole placement(PPP) is presented. This intermittent predictive pole placement algorithm is illustrated in the context of a non-linear pendulum-on-cart system