Dual Heuristic Programming for Optimal Control of Continuous-Time Nonlinear Systems Using Single Echo State Network

Liu, Chong; Zhang, Huaguang; Luo, Yanhong; Su, Hanguang

doi:10.1109/tcyb.2020.2984952

Cited by 26 publications

(8 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They treated the interconnected terms between the subsystems as the disturbances added to the system dynamics. Liu et al [16] presented an improved algorithm to solve the optimal control problem of nonlinear systems with the Hamilton-Jacobi-Bellman (HJB) equation approximated by an ESN to solve the optimal control problem. In inference-based modeling, explicit knowledge regarding the structure of the mathematical model is not required.…”

Section: Related Workmentioning

confidence: 99%

Echo State Network Based Model Predictive Control for Active Vibration Control of Hybrid Electric Vehicle Powertrains

Ogawa

Takahashi

2021

Applied Sciences

View full text Add to dashboard Cite

Reservoir computing refers to a computational framework based on recurrent neural networks that can process time-series data. In an echo state network (ESN), which is a type of reservoir computing framework, the reservoir consists of a recursive network of artificial neurons with nonlinear activation functions. A model predictive control (MPC) technique can determine the control signals by solving the optimization problem of a system using the finite-time domain of each control period. However, real-time optimization cannot be achieved unless the optimal control problem can be solved within the next control period. To overcome this limitation, we propose a new control method based on MPC that explicitly incorporates the predicted disturbance of a time-varying trajectory using ESN to achieve the active vibration control of hybrid electric vehicle (HEV) powertrains. Once the ESN has been trained, the associated MPC explicitly satisfies the constraints over a moving horizon without further training. Instead of completing the real-time optimization within the control period, ESN predicts the future disturbance and applies it to the MPC in the future control period. Based on the predicted future disturbance, the system calculates the optimal control signals required for the future. Thus, real-time control can be realized because the optimal signals are determined before the subsequent control period occurs. The proposed method can be implemented in MPC even if the control period is too short to optimize as long as the disturbance can be reasonably measured and predicted. In this study, the simulation approach was demonstrated using the engine start condition in an HEV powertrain. The importance of this study is that the limitation of MPC relevant to real-time optimization can be relaxed by applying our proposed method.

show abstract

Section: Related Workmentioning

confidence: 99%

Echo State Network Based Model Predictive Control for Active Vibration Control of Hybrid Electric Vehicle Powertrains

Ogawa

Takahashi

2021

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…Here, a single ESN is designed to implement the ADP method by approximating the optimal cost function and the optimal control input simultaneously, which can obtain better control performance. In other words, the single ESN not only is easy to construct, but also can effectively reduce the computational burden and improve the real-time computation [29]. The main contributions of this paper are listed as follows:…”

Section: Introductionmentioning

confidence: 99%

Optimal Frequency Control for Virtual Synchronous Generator Based AC Microgrids via Adaptive Dynamic Programming

Zhang

Sun

Zhou

et al. 2023

IEEE Trans. Smart Grid

View full text Add to dashboard Cite

This paper proposes a novel virtual synchronous generator (VSG) controller for converters in AC microgrids (MGs). Such controller improves the control cost and DC-side energy requirements, while considering the system non-linearity for frequency support. First, the frequency dynamics of the MG, which are analytically studied based on the VSG with a secondary frequency controller, are formulated as a nonlinear state space representation. In this later, the reciprocal of the inertia is modeled as the control input. Correspondingly, a cost function is defined by comprehensively considering the angular deviation, frequency deviation, rate of change of the frequency (RoCoF), and a discount factor, which can retain a tradeoff between the critical frequency bounds and the required control energy. Following, the optimal frequency regulation problem is solved by using an online adaptive dynamic programming (ADP) method, where a single echo state network (ESN) is constructed to approximate the optimal cost function and the optimal control input to significantly reduce the computational burden and improve the real-time computation. Finally, simulation results demonstrate that the frequency response of the system is significantly improved, while also retaining more DCside energy.

show abstract

“…Sometimes the bioactivity of one heterocyclic compound can be slightly improved through the incorporation of some pharmacophores in the structure of its derivatives [24] or by establishing a synergic effect with another heterocyclic ring by bridging one to another ring, as could be done through an Nheterocyclic-fusion between them. [25] As a consequence, some heterocycles such as thiazolidine and dioxopiperazine can be fused into derivatives with potential biological activity.…”

Section: Introductionmentioning

confidence: 99%

“…They were given the abbreviated names ATCAAs [20][21][22][23] and SMART. [24] In these compounds, carbonyl and p-aryl substituents (CH 3 , NH 2 , F) showed to be important for their biological activity (Figure 1).…”

Section: Introductionmentioning

confidence: 99%

New Heterofused Thiazolo/Pyrazinedione Hybrids as Promising Building Blocks for Anticancer Drug Development: Synthesis, Biological and Drug‐Likeness Evaluation

et al. 2023

View full text Add to dashboard Cite

A new series of heterofused thiazolo/pyrazinedione hybrids were designed, synthetized and their cytotoxicity potential was evaluated against different cancer cell lines. Besides, drug‐likeness and in silico ADME/Tox studies were carried out using free server tools. The heterofused hybrids 3‐aryl‐thiazolo[3,4‐a]pyrazine‐5,8‐diones 3 a–o were obtained in moderate to good yields (30–80 %) and with high diastereomeric ratio. Notably, hybrids 3 g–j showed good cytotoxic effect on Hep‐G2 cancer cells IC50 (28.6±4.9 μM, 54.2±15.4 μM, 95.2±1.9 μM, 68.6±1.6 μM) respectively, while compounds 3 l–m were cytotoxic on B16F10 melanoma cancer cells IC50 (20.9±5.3 μM, 30.0±6.4 μM). Furthermore, the new compounds were relatively non‐toxic on Vero cells. In silico drug‐likeness and ADME/Tox studies suggest optimal pharmacokinetic profile for all hybrids. Altogether, these new heterofused hybrids could be considered as promising scaffolds in cancer chemotherapy.

show abstract

Dual Heuristic Programming for Optimal Control of Continuous-Time Nonlinear Systems Using Single Echo State Network

Cited by 26 publications

References 38 publications

Echo State Network Based Model Predictive Control for Active Vibration Control of Hybrid Electric Vehicle Powertrains

Echo State Network Based Model Predictive Control for Active Vibration Control of Hybrid Electric Vehicle Powertrains

Optimal Frequency Control for Virtual Synchronous Generator Based AC Microgrids via Adaptive Dynamic Programming

New Heterofused Thiazolo/Pyrazinedione Hybrids as Promising Building Blocks for Anticancer Drug Development: Synthesis, Biological and Drug‐Likeness Evaluation

Contact Info

Product

Resources

About