. "RIV/70883521:28140/09:63507941!RIV10-MSM-28140___" . . "Self-tuning control of nonlinear servo system: comparison of LQ and predictive approach"@en . "[B3D8176B4600]" . . . "17th Mediterranean Conference on Control and Automation" . "Self-tuning control; LQ control; Predictive control; Nonlinear system; Servo system; Real-time control."@en . . . . . . . "Thessaloniki, Greece" . "340703" . . . "New Jersey" . "4"^^ . "2009-06-26+02:00"^^ . . "Self-tuning control of nonlinear servo system: comparison of LQ and predictive approach" . "Chalupa, Petr" . "Bob\u00E1l, Vladim\u00EDr" . "The majority of processes met in the industrial practice have stochastic characteristics and eventually they embody nonlinear behaviour. Traditional fixed controllers cannot deal with this. One possible alternative for improving the quality of control for such processes is the use of adaptive control systems. Different approaches were proposed and utilized. One successful approach is represented by self-tuning controller (STC). This approach is also called system with indirect adaptation (with direct identification). The main idea of an STC is based on the combination of a recursive identification procedure and a selected controller synthesis. In this paper, the standard STC (non-predictive) approach is verified and compared with STC based on the Model Predictive Control (MPC). The verification of both methods was implemented by the real-time control of a highly nonlinear laboratory model, the DR300 Speed Control with Variable Load."@en . "Self-tuning control of nonlinear servo system: comparison of LQ and predictive approach" . . "978-1-4244-4685-8" . "6"^^ . "4"^^ . "Dost\u00E1l, Petr" . . "IEEE - Inst Electrical Electronics Engineers Inc." . . "Kubal\u010D\u00EDk, Marek" . . "RIV/70883521:28140/09:63507941" . . . . . "28140" . "The majority of processes met in the industrial practice have stochastic characteristics and eventually they embody nonlinear behaviour. Traditional fixed controllers cannot deal with this. One possible alternative for improving the quality of control for such processes is the use of adaptive control systems. Different approaches were proposed and utilized. One successful approach is represented by self-tuning controller (STC). This approach is also called system with indirect adaptation (with direct identification). The main idea of an STC is based on the combination of a recursive identification procedure and a selected controller synthesis. In this paper, the standard STC (non-predictive) approach is verified and compared with STC based on the Model Predictive Control (MPC). The verification of both methods was implemented by the real-time control of a highly nonlinear laboratory model, the DR300 Speed Control with Variable Load." . . "P(1M0567), Z(MSM7088352101)" . "Self-tuning control of nonlinear servo system: comparison of LQ and predictive approach"@en . . .