Stabilization and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si2.gif" display="inline" overflow="scroll"><mml:msub><mml:mrow><mml:mi>H</mml:mi></mml:mrow><mml:mrow><mml:mi>∞</mml:mi></mml:mrow></mml:msub></mml:math> control of nonlinear port-controlled Hamiltonian systems subject to actuator saturation

Wei, Airong; Wang, Yuzhen

doi:10.1016/j.automatica.2010.08.001

Cited by 59 publications

(19 citation statements)

References 17 publications

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“…In the experimental section of the paper, we show that our method is also robust to unmodeled nonlinearities, such as control input saturation. Control input saturation in PBC for PH systems has been addressed explicitly in the literature [10], [11], [12], [13], [14], [15], [16]. We show that our approach solves the problem of control input saturation on the learning side without the need of augmenting the model-based PBC.…”

Section: Reinforcement Learning For Port-hamiltonian Systemsmentioning

confidence: 81%

“…Our approach is that we will use the PDE (10) and split it into an assignable, parameterizable part and an unassignable part that satisfies the matching condition. In this way, it is possible to parameterize the desired closed-loop Hamiltonian H d (x) and simultaneously satisfy (10). After that, we parameterize the damping matrix K(x).…”

Section: Energy-balancing Actor-criticmentioning

confidence: 99%

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Reinforcement Learning for Port-Hamiltonian Systems

Sprangers

Babuška

Nageshrao

et al. 2015

IEEE Trans. Cybern.

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Abstract-Passivity-based control (PBC) for port-Hamiltonian systems provides an intuitive way of achieving stabilization by rendering a system passive with respect to a desired storage function. However, in most instances the control law is obtained without any performance considerations and it has to be calculated by solving a complex partial differential equation (PDE). In order to address these issues we introduce a reinforcement learning approach into the energy-balancing passivity-based control (EB-PBC) method, which is a form of PBC in which the closed-loop energy is equal to the difference between the stored and supplied energies. We propose a technique to parameterize EB-PBC that preserves the systems's PDE matching conditions, does not require the specification of a global desired Hamiltonian, includes performance criteria, and is robust to extra non-linearities such as control input saturation. The parameters of the control law are found using actor-critic reinforcement learning, enabling learning near-optimal control policies satisfying a desired closedloop energy landscape. The advantages are that near-optimal controllers can be generated using standard energy shaping techniques and that the solutions learned can be interpreted in terms of energy shaping and damping injection, which makes it possible to numerically assess stability using passivity theory. From the reinforcement learning perspective, our proposal allows for the class of port-Hamiltonian systems to be incorporated in the actor-critic framework, speeding up the learning thanks to the resulting parameterization of the policy. The method has been successfully applied to the pendulum swing-up problem in simulations and real-life experiments.

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Section: Reinforcement Learning For Port-hamiltonian Systemsmentioning

confidence: 81%

Section: Energy-balancing Actor-criticmentioning

confidence: 99%

Reinforcement Learning for Port-Hamiltonian Systems

Sprangers

Babuška

Nageshrao

et al. 2015

IEEE Trans. Cybern.

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“…In addition, the above results didn't consider the problem of actuator saturation. However, the actuator saturation is a potential factor of system performance deterioration and system instability in [15,16]. Because the redundant actuator shares the responsibility for the failure actuator in the fault-tolerant control system, the actuator is more liable to enter the saturated region.…”

Section: Introductionmentioning

confidence: 99%

The Co-design Method for Robust Satisfactory H / H Fault-tolerant Event-triggered Control of NCS with α - Safety Degree

Li¹,

Li²

2015

TOAUTOCJ

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Based on discrete event-triggered communication scheme (DETCS), this paper is concerned with the satisfactory H ! / H 2 event-triggered fault-tolerant control problem for networked control system (NCS) with α -safety degree and actuator saturation constraint from the perspective of improving satisfaction of fault-tolerant control and saving network resource. Firstly, the closed-loop NCS model with actuator failures and actuator saturation is built based on DETCS;Secondly, based on Lyapunov-Krasovskii function and the definition of α -safety degree given in the paper, a sufficient condition is presented for NCS with the generalized H 2 and H ! performance, which is the contractively invariant set of fault-tolerance with α -safety degree, and the co-design method for event-triggered parameter and satisfactory faulttolerant controller is also given in this paper. Moreover, the simulation example verifies the feasibility of improving system satisfaction and the effectiveness of saving network resource for the method. Finally, the compatibility analysis of the related indexes is also discussed and analyzed.

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“…These nonlinearities may bring limit cycles or other unexpected influences on the systems, and thus undermine the stability of the systems. In [10] and [11], some asymptotical stability results were given for the systems with generalized overflow characteristics and partial state saturation, respectively. Besides these, another matter to cause instability of the filtering systems under study is time delay.…”

Section: Introductionmentioning

confidence: 99%

Robust H∞ Filter Design for Time-delay Systems with Saturation

Hong

Wang

2013

Int. J. Autom. Comput.

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This paper investigates the H∞ filtering problem for a class of linear continuous-time systems with both time delay and saturation. Such systems have time delay in their state equations and saturation in their output equations, and their process and measurement noises have unknown statistical characteristics and bounded energies. Based on the Lyapunov-Krasovskii stability theorem and the linear matrix inequalities (LMIs) technique, a generalized dynamic filter architecture is proposed, and a filter design method is developed. The linear H∞ filter designed by the method can guarantee the H∞ performance. The parameters of the designed filter can be obtained by solving a kind of LMI. An illustrative example shows that the design method proposed in this paper is very effective.

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Stabilization and H∞ control of nonlinear port-controlled Hamiltonian systems subject to actuator saturation

Cited by 59 publications

References 17 publications

Reinforcement Learning for Port-Hamiltonian Systems

Reinforcement Learning for Port-Hamiltonian Systems

The Co-design Method for Robust Satisfactory H / H Fault-tolerant Event-triggered Control of NCS with α - Safety Degree

Robust H∞ Filter Design for Time-delay Systems with Saturation

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