$PID$	Proportional–integral–derivative control
$RBFNN$	Radial basis neural network
$RL$	Reinforcement learning
$SARSA$	State-Action-Reward-State-Action
Q	The Value of Action in reinforcement learning
$DRL$	Deep reinforcement learning
$DNN$	Deep neural networks
$DQN$	Deep Q network
$PG$	Policy gradient
$DDPG$	Deep deterministic policy gradient
$ID$	Integral differential compensator
$T_m$	The magnetic force
y	The working air gap in micropositioner
$I_c$	The excitation current in micropositioner
$EMA$	The electron-magnetic actuator
$V_i$	The input voltage from the electron-magnetic actuator
R	The resistance of the coil in micropositioner
H	The coil inductance in micropositioner
u	The control input
D	The lumped system disturbance
$ASMDO$	Adaptive Sliding Mode Disturbance Observer
$s_t$	The state at time t in reinforcement learning
$a_t$	The action at time t in reinforcement learning
$r_t$	The reward at time t in reinforcement learning
$ReLU$	Rectified linear unit activation function
$tanh$	Hyperbolic tangent activation function