CONTROL FRAMEWORK OF MODEL PREDICTIVE CONTROL AND ADAPTIVE TRACKING USING SHARED NEURAL NETWORK DYNAMICS MODEL

• Main Authors: KIM TAE KYUNG, LEE WON SUK, LEE HO JIN, HONG SEONG IL
• Format: Patent
• Language: English; Korean
• Published: 21.09.2022
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE ORDIFFERENT FUNCTION; CONTROL OR REGULATING SYSTEMS IN GENERAL; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; CONTROLLING; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS; PERFORMING OPERATIONS; PHYSICS; REGULATING; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TOTHE CONTROL OF A PARTICULAR SUB-UNIT; SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES; TRANSPORTING; VEHICLES IN GENERAL

The present invention relates to a model predictive control method of an autonomous vehicle which comprises the following steps of: modeling an expected trajectory after a certain point in time by linearizing a dynamics model for predicting motion of the autonomous vehicle through a model predictive controller; calculating a feedback gain corresponding to the expected trajectory through a path following controller; and compensate-inputting the feedback gain to the model predictive controller. According to the present invention, the dynamic model of the model predictive controller can be used as it is and applied to all controllers. 본 발명은 모델 예측 제어기를 통해 자율주행 차량의 운동을 예측하기 위한 동역학 모델을 선형화하여 일정 시점 이후의 예상 궤적을 모델링하는 단계, 경로 추종 제어기를 통해 상기 예상 궤적에 해당하는 피드백 게인(Feedback gain)을 산출하는 단계 및 상기 피드백 게인을 상기 모델 예측 제어기에 보상 입력하는 단계를 포함하는 자율주행 차량의 모델 예측 제어 방법으로서, 본 발명에 의하면, 모델 예측 제어기의 동역학 모델을 그대로 사용하여 모든 제어기에 적용 가능하다.