When the process is highly uncertain, even linear minimum phase systems must sacrifice desirable feedback control benefits to avoid an excessive ‘cost of feedback’, while preserving the robust stability. In this paper, the problem of supervisory based switching Quantitative Feedback Theory (QFT) control is proposed for the control of highly uncertain plants. According to this strategy, the unce...

Optimal control theory and its more recent extension, optimal feedback control theory, provide valuable insights into the flexible and task-dependent control of movements. Here, we focus on the problem of coordination, defined as movements that involve multiple effectors (muscles, joints or limbs). Optimal control theory makes quantitative predictions concerning the distribution of work across ...

In this paper a new method for robust decentralised control of large-scale systems using quantitative feedback theory (QFT ) is suggested. For a given largescale system an equivalent descriptor system is defined. Using this representation, closed-loop diagonal dominance sufficient conditions over the uncertainty space are derived. It is shown by appropriately choosing output disturbance rejecti...

Manually landing an unmanned aerial vehicle presents unique challenges since unmanned vehicle pilots require extensive training to become proficient in the landing task. Operators must therefore choose between a pilot controlling the vehicle from a ground station, or procurement of an automatic landing system. Although several autoland controllers exist for small or micro unmanned vehicles and ...

This paper outlines a dynamic theory of development and adaptation in neural networks with feedback connections. Given input ensemble, the connections change in strength according to an associative learning rule and approach a stable state where the neuronal outputs are decorrelated. We apply this theory to primary visual cortex and examine the implications of the dynamical decorrelation of the...