Compressive-Sensed Image Coding via Multi-layer Closed-Loop Prediction

2019 ◽  
Author(s):  
Zan Chen ◽  
Xingsong Hou ◽  
Ling Shao ◽  
Yuan Huang
Keyword(s):  
Image Coding ◽  
Closed Loop ◽  
Loop Prediction

The utilization of closed-loop prediction for dynamic real-time optimization

2017 ◽  
Vol 95 (10) ◽  
pp. 1968-1978 ◽  
Author(s):  
Mohammad Z. Jamaludin ◽  
Hao Li ◽  
Christopher L. E. Swartz
Keyword(s):  
Real Time ◽  
Closed Loop ◽  
Loop Prediction ◽  
Time Optimization ◽  
Real Time Optimization

scholarly journals IMPROVED CONSTRAINT HANDLING APPROACH FOR PREDICTIVE FUNCTIONAL CONTROL USING AN IMPLIED CLOSED-LOOP PREDICTION

2021 ◽  
Vol 22 (1) ◽  
pp. 323-338
Author(s):  
Muhammad Abdullah ◽  
John Anthony Rossiter ◽  
Alia Farhana Abdul Ghaffar
Keyword(s):  
Closed Loop ◽  
Open Loop ◽  
Constraint Handling ◽  
Constant Input ◽  
Loop Prediction ◽  
Predictive Functional Control ◽  
Simple Alternative ◽  
Ill Posed ◽  
Functional Control ◽  
Process Constraints

Predictive Functional Control is a simple alternative to the traditional PID controller which has the capability to handle process constraints more systematically. Nevertheless, the most basic form of PFC has suffered from ill-posed prediction due to its simplicity in formulation and assumption of constant future input dynamics. Although some constraints can be satisfied, nevertheless the performance may be very conservative due to this issue. The main objective of this paper is to improve the constrained performance of a PFC controller with a minimum modification of the existing formulation. Specifically, a novel constraint handling approach for PFC is proposed based on an implied closed-loop prediction. Instead of assuming a constant input as deployed in the conventional open-loop prediction, the implied closed-loop input dynamics are utilised to detect future constraint violations. In addition, a future perturbation is introduced into the prediction structure as an extra degree of freedom for satisfying the constraints. Two simulation results confirm that the proposed approach gives far less conservative constraint handling and thus better control performance compared to the nominal PFC. Furthermore, this novel implementation also alleviates the well-known tuning difficulties and prediction inconsistency issues that are associated with conventional PFC when handling constraints. ABSTRAK: Kawalan Kefungsian Ramalan adalah alternatif mudah kepada kawalan tradisional PID yang mempunyai kekangan keupayaan bagi mengawal proses secara lebih tersusun. Namun, keadaan paling asas pada kesan PFC adalah daripada ramalan tak teraju-rapi yang disebabkan oleh formula ringkas dan anggapan dinamik input yang sama bagi masa depan. Walau kekangan ini dapat diatasi, namun prestasi akan berubah secara konservatif disebabkan oleh isu ini. Objektif utama kajian ini adalah bagi membaiki kekangan prestasi kawalan PFC dengan modifikasi minimum formula yang ada. Secara spesifik, pendekatan nobel kawalan PFC dicadangkan berdasarkan ramalan lingkaran-tertutup. Selain anggapan input tetap seperti yang dilakukan pada ramalan lingkaran-terbuka yang konservatif, dinamik input yang dibuat pada lingkaran-tertutup telah digunakan bagi mengesan kekangan masa depan yang bertentangan. Tambahan, gangguan yang bakal berlaku pada masa depan telah diperkenalkan ke dalam struktur ramalan sebagai tambahan darjah pada kebebasan bagi mengatasi kekangan. Dua dapatan simulasi kajian menyetujui pendekatan yang dicadangkan dan menyebabkan sangat kurang kekangan pengendalian pada sistem konservatif, oleh itu kawalan yang lebih bagus pada prestasi  berbanding pada PFC nominal. Selain itu, pendekatan nobel ini juga menghilangkan kesukaran pelarasan yang dikenali ramai dan ramalan isu tidak konsisten yang terdapat pada PFC konvensional apabila mengendali kekangan.

Mobility Modeling and Data-Driven Closed-Loop Prediction in Bike-Sharing Systems

2019 ◽  
Vol 20 (12) ◽  
pp. 4488-4499 ◽  
Author(s):  
Zidong Yang ◽  
Jiming Chen ◽  
Ji Hu ◽  
Yuanchao Shu ◽  
Peng Cheng
Keyword(s):  
Closed Loop ◽  
Data Driven ◽  
Mobility Modeling ◽  
Loop Prediction ◽  
Bike Sharing

scholarly journals Motion Planning in Complex Environments Using Closed-loop Prediction

2008 ◽  
Author(s):  
Yoshiaki Kuwata ◽  
Justin Teo ◽  
Sertac Karaman ◽  
Gaston Fiore ◽  
Emilio Frazzoli ◽  
...  
Keyword(s):  
Motion Planning ◽  
Closed Loop ◽  
Complex Environments ◽  
Loop Prediction
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