Predictive joint-action model: A hierarchical predictive approach to human cooperation
نویسندگان
چکیده
منابع مشابه
A distributed optimization - based approach for hierarchical model predictive
We present a hierarchical model predictive control approach for large-scale systems based on dual decomposition. The proposed scheme allows coupling in both dynamics and constraints between the subsystems and generates a primal feasible solution within a finite number of iterations, using primal averaging and a constraint tightening approach. The primal update is performed in a distributed way ...
متن کاملModel Predictive Control and Stability Analysis of a Standing Biped with Toe-Joint
In this paper standing balance control of a biped with toe-joint is presented. The model consists of an inverted pendulum as the upper body and the foot contains toe-joint. The biped is actuated by two torques at ankle-joint and toe-joint to regulate the upper body in upright position. To model the interaction between foot and the ground, configuration constraints are defined and utilized. To s...
متن کاملGame Approach to Distributed Model Predictive Control
In this paper, a novel distributed model predictive control scheme based on Nash optimality is presented for largescale processes, in which the on-line optimization of the whole system is decomposed into that of several small cooperative subsystems in distributed structures. The relevant computational convergence, closed-loop performance and the nominal stability for distributed model predictiv...
متن کاملModel Predictive Impedance Control: A Model for Joint Movement.
Impedance control has been suggested as the strategy employed by the central nervous system to control human postures and movements. A realization of this strategy is presented that uses a model predictive control algorithm as a higher motor controller. External disturbances are explicitly included in the model. The combination of 3 key factors-joint impedance control, model predictive controll...
متن کاملTwo-stage Optimization Approach to Robust Model Predictive Control with a Joint Chance Constraint
This report proposes a new two-stage optimization method for robust Model Predictive Control (RMPC) with Gaussian disturbance and state estimation error. Since the disturbance is unbounded, it is impossible to achieve zero probability of violating constraints. Our goal is to optimize the expected value of a objective function while limiting the probability of violating any constraints over the ...
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: Psychonomic Bulletin & Review
سال: 2017
ISSN: 1069-9384,1531-5320
DOI: 10.3758/s13423-017-1393-6