Comparison of Deep Reinforcement Learning and Model Predictive Control for Adaptive Cruise Control
نویسندگان
چکیده
منابع مشابه
Adaptive Simplified Model Predictive Control with Tuning Considerations
Model predictive controller is widely used in industrial plants. Uncertainty is one of the critical issues in real systems. In this paper, the direct adaptive Simplified Model Predictive Control (SMPC) is proposed for unknown or time varying plants with uncertainties. By estimating the plant step response in each sample, the controller is designed and the controller coefficients are directly ca...
متن کاملConcurrent Learning Adaptive Model Predictive Control
A concurrent learning adaptive-optimal control architecture for aerospace systems with fast dynamics is presented. Exponential convergence properties of concurrent learning adaptive controllers are leveraged to guarantee a verifiable learning rate while guaranteeing stability in presence of significant modeling uncertainty. The architecture switches to online-learned model based Model Predictiv...
متن کاملthe relationship between locus of control and iranian efl university students’ beliefs about language learning
this exploratory study aimed to investigate a possible relationship between learners’ beliefs about language learning and one of their personality traits; that is,locus of control (loc). both variables, beliefs and locus of control, are assumed to influence the language learning process. the internal control index (ici) and the beliefs about language learning inventory (balli) were administered...
Benchmarking Deep Reinforcement Learning for Continuous Control
Recently, researchers have made significant progress combining the advances in deep learning for learning feature representations with reinforcement learning. Some notable examples include training agents to play Atari games based on raw pixel data and to acquire advanced manipulation skills using raw sensory inputs. However, it has been difficult to quantify progress in the domain of continuou...
متن کاملStructure Learning in Motor Control: A Deep Reinforcement Learning Model
Motor adaptation displays a structure-learning effect: adaptation to a new perturbation occurs more quickly when the subject has prior exposure to perturbations with related structure. Although this ‘learning-to-learn’ effect is well documented, its underlying computational mechanisms are poorly understood. We present a new model of motor structure learning, approaching it from the point of vie...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Intelligent Vehicles
سال: 2021
ISSN: 2379-8904,2379-8858
DOI: 10.1109/tiv.2020.3012947