Robust control and μ analysis of active pneumatic suspension

A Disturbance Attenuation Approach for the Control of Differential-Algebraic Systems

“…Some of the challenges in control of air suspensions are due to nonlinearities and uncertainties in the model equations, which restricts their use to basic operations such as vehicle lifting for passenger entry and exit or to optimize the comfort, while other advanced control tasks such as isolating road harshening are provided by different suspension systems. However, according to many authors (see [23], [24], [25] and references therein for more insight on this topic), robust control which solve the aforementioned problems has not been solved in an analytical way.…”

Robust µ control and repetitive control for precision motion control of a pneumatic actuating table

“…By setting uncertain bounds in the model and adjusting appropriate weightings, this technique offers an acceptable trade-off between performance and robustness, which is suitable for servo design of uncertain and complex pneumatic systems. [7][8][9][10][11][12][13][14] A nominal plant model is mandatory in the H N control design process and can be obtained by performing standard system identification techniques. 14,16 The nonlinearities and unmodeled dynamics can be simply treated as model uncertainties to formulate robust control problems.…”

“…Recent studies regarding robust control of pneumatic actuating systems can be found in three primary groups: adaptive robust control, 1,2 sliding mode control, 3–6 and H ∞ control-related techniques. 7–14 To perform state feedback control based on a limited output measurement, deriving an accurate mathematical model or adding extra sensors is necessary for the first two methods. However, because air compressibility and thermal influences in parameters change, for implementation, building a perfect model to perform such model-based design is difficult.…”

“…By setting uncertain bounds in the model and adjusting appropriate weightings, this technique offers an acceptable trade-off between performance and robustness, which is suitable for servo design of uncertain and complex pneumatic systems. 7–14…”

“…A nominal plant model is mandatory in the H ∞ control design process and can be obtained by performing standard system identification techniques. 14,16 The nonlinearities and unmodeled dynamics can be simply treated as model uncertainties to formulate robust control problems. For enhanced system ID results and control performance, another common technique is to close the original open-loop system for a guaranteed stable model by first applying a classical feedback controller.…”