A proof of stability of model-free control

Delaleau, Emmanuel

doi:10.1109/norbert.2014.6893908

Cited by 11 publications

(4 citation statements)

References 22 publications

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“…Based on the numerical knowledge of 𝐹, the control is computed using ( 21) as a simple cancellation of the nonlinear terms, as described in 𝐹, in addition to a closed loop tracking of a reference trajectory. More specifically, using the latest 𝐹, the intelligent proportional control law is given by [59]:…”

Section: Power Allocation Of Building Tcls Using Medel-free Controlmentioning

confidence: 99%

Hierarchical Model-Free Transactive Control of Building Loads to Support Grid Services

Olama

Amasyali

Chen

et al. 2022

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Section: Power Allocation Of Building Tcls Using Medel-free Controlmentioning

confidence: 99%

Hierarchical Model-Free Transactive Control of Building Loads to Support Grid Services

Olama

Amasyali

Chen

et al. 2022

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“…Based on the numerical knowledge of , the control is computed using (21) as a simple cancellation of the nonlinear terms, as described in , in addition to a closedloop tracking of a reference trajectory. More specifically, using the latest , the intelligent proportional control law is given by [34]:…”

Section: = ∀mentioning

confidence: 99%

Hierarchical Model-Free Transactional Control of Building Loads to Support Grid Services

et al. 2020

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A transition from generation on demand to consumption on demand is one of the solutions to overcome the many limitations associated with the higher penetration of renewable energy sources. Such a transition, however, requires a considerable amount of load flexibility in the demand side. Demand response (DR) programs can reveal and utilize this demand flexibility by enabling the participation of a large number of grid-interactive efficient buildings (GEB). Existing approaches on DR require significant modelling or training efforts, are computationally expensive, and do not guarantee the satisfaction of end users. To address these limitations, this paper proposes a scalable hierarchical model-free transactional control approach that incorporates elements of virtual battery, game theory, and model-free control (MFC) mechanisms. The proposed approach separates the control mechanism into upper and lower levels. The MFC modulates the flexible GEB in the lower level with guaranteed thermal comfort of end users, in response to the optimal pricing and power signals determined in the upper level using a Stackelberg game integrated with aggregate virtual battery constraints. Additionally, the usage of MFC necessitates less burdensome computational and communication requirements, thus, it is easily deployable even on small embedded devices. The effectiveness of this approach is demonstrated through a large-scale case study with 10,000 heterogenous GEB. The results show that the proposed approach can achieve peak load reduction and profit maximization for the distribution system operator, as well as cost reduction for end users while maintaining their comfort. INDEX TERMS Demand response, model-free control, Stackelberg game, thermostatically controlled loads, transactive control, virtual battery K. Amasyali et al.: Hierarchical Model-Free Transactional Control of Building Loads to Support Grid Services

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“…In our case, for identifying the perturbation online, two ultra-local models could be implemented by subtracting ϕ ^ from the closed loop part. Delaleau 31 detailed the proof of stability of proposed control in presence of algebraic estimator. The outputs variables of the active suspension system are chosen as g = [ z s z u ] that can be calculated after double integration process from two vertical accelerometers.…”

Section: I-lqr Designmentioning

confidence: 99%

Intelligent optimal controller design applied to quarter car model based on non-asymptotic observer for improved vehicle dynamics

Haddar

Chaari

Başlamışlı

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part I:

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A novel active suspension control strategy is introduced to improve dynamic response of vehicle suspension systems. The proposed algorithm is a fusion of classical controller design methods together with an online observer and is based on the cancelation of system disturbances. The operational calculus method and the differential algebraic theory are applied to build the observer/compensator that is appended to the classical linear quadratic regulator. An ultra-local model based on linear algebraic rules is presented avoiding the use of a precise mathematical model while guaranteeing the stability of the overall system. Simplicity of implementation, low power demand and significant enhancement of active suspension performance are the observed features of the proposed controller. The numerical simulations illustrate the effectiveness and the robustness against sprung mass variation of the proposed control method compared to proportional–integral–derivative controller, intelligent proportional–derivative controller, linear quadratic regulator and active disturbance rejection—linear quadratic regulator.

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A proof of stability of model-free control

Cited by 11 publications

References 22 publications

Hierarchical Model-Free Transactive Control of Building Loads to Support Grid Services

Hierarchical Model-Free Transactive Control of Building Loads to Support Grid Services

Hierarchical Model-Free Transactional Control of Building Loads to Support Grid Services

Intelligent optimal controller design applied to quarter car model based on non-asymptotic observer for improved vehicle dynamics

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