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Data-driven, model-free control strategies leverage statistical or learning techniques to design controllers based on data instead of dynamic models. We have previously introduced the dissipativity learning control (DLC) method, where the dissipativity property is learned from the input-output trajectories...
Besides, the discrete I/O-driven controllers were developed in (Han et al., 2019; Liao et al., 2019), where the Pseudo-Partial Derivative technology is utilized to dynamically linearize the nonlinear system along the dynamic operation points. Nevertheless, most of the data-driven controllers ...
As mentioned above, most of the control methods are model-based. The dynamic model of the exoskeleton has been already known before the controller design or the model structure is known and parameters can be estimated. That paves the way for more and more complicated controllers. Since the exo...
Experiments corroborate the effectiveness and superiority of the presented method over model-based controllers including PI, state feedback, and optimal robust linear quadratic integral controllers in terms of various metrics. 展开 关键词: Z-source data-driven model-free adaptive control non-minimum ...
this paper proposes a data-driven iterative learning model predictive control method based on an adaptive iterative extended state observer (IESO) for designing melt temperature and crystal diameter learning controllers with disturbance suppression... JC Ren,D Liu,Y Wan - 《Journal of the Franklin In...
Model Reference Adaptive Control of Satellite Spin Anti-Lock Braking Using Extremum Seeking Control Adaptive MPC Control of Nonlinear Chemical Reactor Using Online Model Estimation Tune Field-Oriented Controllers Using Closed-Loop PID Autotuner Block See...
the structure of the controller is fixed and a few control parameters are optimized using data collected on the fly. A widely known example is the auto-tuning of PID controllers33. Behavior-based techniques exploit a trajectory-based (or behavioral) representation of the system, and data that ...
As mentioned above, most of the control methods are model-based. The dynamic model of the exoskeleton has been already known before the controller design or the model structure is known and parameters can be estimated. That paves the way for more and more complicated controllers. Since the exo...
Stemming from this intriguing approach, also considering the well known robustness properties of SM controllers [18], [19], a more rigorous stability analysis is here presented, carried out using not the real (but unavailable) model of the plant, differently from [12], but its estimated ...