AVS 56th International Symposium & Exhibition
    Plasma Science and Technology Thursday Sessions
       Session PS2-ThA

Paper PS2-ThA9
Real Time Control of an Inductively Coupled Plasma Simulation

Thursday, November 12, 2009, 4:40 pm, Room B2

Session: Plasma Diagnostics, Sensors, and Control II
Presenter: B.J. Keville, Dublin City University, Ireland
Authors: B.J. Keville, Dublin City University, Ireland
M.M. Turner, Dublin City University, Ireland
Correspondent: Click to Email

Process yield in many plasma assisted processes may be improved significantly by real time, closed loop control of certain plasma species. This paper describes the closed loop control of a low pressure, inductively coupled plasma simulation. The plasma simulation consists of a global model of the plasma chemistry coupled to an equivalent circuit. The equivalent circuit incorporates an impedance matching box and an model of power coupling from the antenna into the plasma which has been derived from the wave equation and the two term solution to the Boltzmann equation. In addition, mass flow controller models and gas flow transport delays are included in the simulation. The design of effective, real time, closed loop control algorithms is facilitated by simple, control-oriented, dynamical models of the relationship between actuators (inputs) and the process quantities to be controlled. The paper will indicate how the parameters of a control algorithm may be determined from the process model (model-based control) in order to guarantee a robustly stable closed loop response. In general, process measurements are noisy and may not provide direct estimates of process quantities to be controlled. For example, estimates of atomic oxygen density obtained from optical emission spectroscopy are ambiguous due to dissociative excitation. Furthermore, many process parameters such as wall sticking coefficients are extremely difficult to estimate and may change due to chamber seasoning. The paper will indicate how an optimal state estimator may be used to improve estimates obtained from optical emission spectroscopy and how such estimates may be used to adapt the control algorithm in real time in order to guarantee process stability despite changes in process parameters.