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Congress 2018

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May 26 – June 1 | Regina, Saskatchewan

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SURFACE OPERATIONS DIVISION

The Surface Operations Division is divided into three branches that support the 6,000 qualified boat crew members in the Auxiliary Surface Program.

Our Safety Branch focuses on ensuring the safe execution of the surface operations mission. The Safety Branch is responsible to collect and analyze national mishap information to identify systemic risks and hazards that might compromise the safety of surface personnel. Working collaboratively with District Staff Officers, local hazards and safety concerns are identified and, combined with the national mishap data to help the Surface Operations Division develop “best safety practices” that address risks and hazards.

Our Safety Branch

The Qualifications Branch leads the development of high quality standards and qualification guidelines that reflect both the rigor of the Coast Guard’s operational standards and the diverse nature of the Auxiliary mission and platform. This branch provides regular review of surface operational doctrine such as policy, training and qualification manuals. Finally, the Qualifications branch organizes and facilitates the CG Auxiliary Standardization (STAN) Team, which promotes an ongoing dialogue with Coast Guard and Auxiliary leadership and supports a nimble response to timely operational issues.

The Qualifications Branch

Within the Surface Division, the Special Projects Branch leads the development of member ready resources, including best practices guides and deliverables in support of safety, qualifications, training and other key components of the Surface Operations Division.

Special Projects Branch

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Within its program management responsibilities the Aviation Division designs and develops program components that focus on safety, aircraft maintenance, continuing education, and currency maintenance for our leaders, pilots and other crewmembers. The Division also provides subject matter expertise and consultation on Auxiliary aviation concerns to Coast Guard headquarters program management leadership, the Chief Director’s office, and NEXCOM. In addition, they also provide consultation and support to the District staff members who are charged with the responsibility for the Aviation operation in the field on Coast Guard and Auxiliary policy, and aviation safety.

The Division has branches in several major areas of expertise, including training, aero medical, flight safety, flight standards, and management . Highly skilled and competent aviators are vital to support safe and effective execution of Coast Guard and CG Auxiliary missions.

training, aero medical, flight safety, flight standards, and management

Our Flight Standards Branch leads the development of high quality standards and qualification guidelines that reflect both the rigor of the Coast Guard’s operational standards and the diverse nature of the Auxiliary mission and platform. The Branch organizes and facilitates the CG Auxiliary Standardization (STAN) Team, which promotes an ongoing dialogue with Coast Guard and Auxiliary leadership to recommend policy.

Figure 10.

The serial system and an alternative system based on direct slave feedback. The internal slave model is delineated by a dashed box. Green blocks represent unchangeable elements of the underlying control loop, while yellow blocks have been added to enable anticipation. () The serial system. An internal model of the system’s dynamics acts as the ’slave’ in AS, while the output of the plant provides delayed self-feedback. The output of the model is a prediction of the future value of the err term, which is used to drive the controller without lag. () Alternative system where the delayed self-feedback is taken directly from the slave with an independent delay that must be tuned to closely match the sum of delays in the system. This entails the removal of feedback from the real slave.

The target is treated as the master, while the slave has the same dynamics as the system described in §2.1 and shown in figure2 , minus the sensory and feedback delays. This constitutes an autonomous system that can be synchronized with the target’s motion. The coupling term (equation( 4.1 )) is added directly to the ˙ x and ˙ y terms of the target dynamics within the slave (equation( 2.4 ), equation ( Slip on Sneakers for Women On Sale Avio Blue Suede leather 2017 55 Santoni 5.5 Santoni Suede leather ylRb9nX
)). The plant itself is treated as a delay between sensing the movement of the target and sensing the end-effector’s response. Theoretically, any sensory or actuation delays (within certain stability bounds) will be compensated by an equal period of anticipation: K [ x target ( t τ ) x plant ( t τ τ f ) ] .

We compare this with an approach where the state of the slave is delayed within the slave model ( τ model ) and fed directly fed back in the coupling, as in figure10 b , in order to demonstrate that our system is not vulnerable to applying anticipation that does not match the true system delay.

4.1. Testing

In order to find the limits of the serial system’s anticipation, the tracking task was simulated over a range of values for and both and , and the lag and lag-adjusted RMSE. This allows the region in which stable anticipation (and thus, accurate tracking) occurs to be plotted as a function of coupling strength and delay. The system was also exposed to a sensory delay that was abruptly doubled in length partway through a movement, and its response compared with that of the system described in figure10 .

The system was simulated over a range of and values while subject to a torque disturbance at a fixed point in each movement. The system stability was also compared against that of the original control loop by exposing both to a step disturbance and recording their response.

The relationship between anticipation time, coupling strength and feedback delay can be seen in figure11 a . The lag between target and end-effector decreases and is replaced by a significant degree of anticipation as the feedback delay τ f is increased. Unlike the parallel system, the tracking performance barely decreases within the region of stable anticipation, as seen in figure11 b .

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