TY - JOUR
T1 - Stability analysis and efficiency of EMPC for Type-1 systems
AU - Aravind, M.A.
AU - Saikumar, Niranjan
AU - Dinesh, N. S.
AU - Rajanna, K.
N1 - Accepted Author Manuscript
PY - 2018
Y1 - 2018
N2 - Experience mapping based predictive controller (EMPC) is a recently developed controller based on the concepts of Human Motor Control. It has been demonstrated to out-perform other classical controllers like proportional-derivative (PD), model reference based adaptive controller (MRAC), linear quadratic regulator (LQR) and the linear quadratic Gaussian (LQG) for both Type-1 and Type-0 systems. This paper analyses the stability and efficiency of EMPC for Type 1 systems. EMPC uses rectangular pulse input as control action for well-damped Type 1 systems and a first order decay input for under-damped Type 1 systems. The simulation results of EMPC for position control of a DC motor with a load coupled through a flexible shaft are presented as a case study to derive and prove the stability criterion. The efficiency of EMPC on a practical system is analysed in terms of energy dissipated in the armature resistance of the motor and the same is compared with PD, MRAC, LQR, LQG controller. Further, the computational cost of EMPC is discussed and compared with traditional controllers from the point of view of implementation.
AB - Experience mapping based predictive controller (EMPC) is a recently developed controller based on the concepts of Human Motor Control. It has been demonstrated to out-perform other classical controllers like proportional-derivative (PD), model reference based adaptive controller (MRAC), linear quadratic regulator (LQR) and the linear quadratic Gaussian (LQG) for both Type-1 and Type-0 systems. This paper analyses the stability and efficiency of EMPC for Type 1 systems. EMPC uses rectangular pulse input as control action for well-damped Type 1 systems and a first order decay input for under-damped Type 1 systems. The simulation results of EMPC for position control of a DC motor with a load coupled through a flexible shaft are presented as a case study to derive and prove the stability criterion. The efficiency of EMPC on a practical system is analysed in terms of energy dissipated in the armature resistance of the motor and the same is compared with PD, MRAC, LQR, LQG controller. Further, the computational cost of EMPC is discussed and compared with traditional controllers from the point of view of implementation.
KW - Computational cost
KW - DC motor
KW - Efficiency
KW - Experience mapping based predictive controller
KW - Flexible shaft
KW - Optimal control system
KW - Position control
KW - Stability
UR - http://resolver.tudelft.nl/uuid:59d5d77a-0ee5-4328-87a4-441e588eb1ed
UR - http://www.scopus.com/inward/record.url?scp=85050261685&partnerID=8YFLogxK
U2 - 10.1007/s40435-018-0461-8
DO - 10.1007/s40435-018-0461-8
M3 - Article
AN - SCOPUS:85050261685
SN - 2195-268X
VL - 7 (2019)
SP - 452
EP - 468
JO - International Journal of Dynamics and Control
JF - International Journal of Dynamics and Control
IS - 2
ER -