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A new method for adaptive-fuzzy control achieves knowledge of the model or modeling error (respectively). stabilization of a quadrotor helicopter in the presence of The technique of e-modification does not. However, in the sinusoidal wind disturbance. Techniques traditionally used in quadrotor simulation an adaptive-fuzzy control technique that adaptive control for robust parameter updates may not be q q sufficient for fuzzy schemes. In particular, e-modification may relies on e-modification for robustness may not perform result in the fuzzy-membership centers drifting to large values satisfactorily. Performance must be sacrificed to halt the when persistent oscillations are present in the input. These center drift. large values can cause control signal chatter, which can be We propose a new robust method that does not require undesirable or even cause instability if they excite unmodeled a sacrifice of performance to halt the center drift. An aldynamics. A new method for robust updates is proposed that as e of performanctoh center drt. Anial prevents this drift in the fuzzy membership centers. In the new ternate set of membersh functon centers i used to guide method, a set of alternate membership function centers guides the adaptation. The alternate set is trained to approximate the adaptation process in order to prevent drift. A Lyapunovsame output without exhibiting any center drift. The fuzzy stability proof ensures the uniform ultimate boundedness of all decoding membership function centers used in the control are signals. A simulation of a quadrotor helicopter demonstrates then kept close to these alternate centers in order to prevent the high performance and robust stability of the new method. drift while maintaining a high level of performance.

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Robots are becoming increasingly relevant to neurosurgeons, extending a neurosurgeon's physical capabilities, improving navigation within the surgical landscape when combined with advanced imaging, and propelling the movement toward minimally invasive surgery. Most surgical robots, however, isolate surgeons from the full range of human senses during a procedure. This forces surgeons to rely on vision alone for guidance through the surgical corridor, which limits the capabilities of the system, requires significant operator training, and increases the surgeon's workload. Incorporating haptics into these systems, ie, enabling the surgeon to "feel" forces experienced by the tool tip of the robot, could render these limitations obsolete by making the robot feel more like an extension of the surgeon's own body. Although the use of haptics in neurosurgical robots is still mostly the domain of research, neurosurgeons who keep abreast of this emerging field will be more prepared to take advantage of it as it becomes more prevalent in operating theaters. Thus, this article serves as an introduction to the field of haptics for neurosurgeons. We not only outline the current and future benefits of haptics but also introduce concepts in the fields of robotic technology and computer control. This knowledge will allow readers to be better aware of limitations in the technology that can affect performance and surgical outcomes, and "knowing the right questions to ask" will be invaluable for surgeons who have purchasing power within their departments.

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