In this thesis I show achievements for precision feedback control of objects inside micro-fluidic systems and for magnetically guided ferrofluids. Essentially, this is about doing flow control, but flow control on the microscale, and further even to nanoscale accuracy, to precisely and robustly manipulate micro and nano-objects (i.e. cells and quantum dots). Target applications include methods to miniaturize the operations of a biological laboratory (lab-on-a-chip), i.e. presenting pathogens to on-chip sensing cells or extracting cells from messy bio-samples such as saliva, urine, or blood; as well as non-biological applications such as deterministically placing quantum dots on photonic crystals to make multi-dot quantum information systems. The particles are steered by creating an electrokinetic fluid flow that carries all the particles from where they are to where they should be at each time step. The control loop comprises sensing, computation, and actuation to steer particles along trajectories. Particle locations are identified in real-time by an optical system and transferred to a control algorithm that then determines the electrode voltages necessary to create a flow field to carry all the particles to their next desired locations. The process repeats at the next time instant. I address following aspects of this technology. First I explain control and vision algorithms for steering single and multiple particles, and show extensions of these algorithms for steering in three dimensional (3D) spaces. Then I show algorithms for calculating power minimum paths for steering multiple particles in actuation constrained environments. With this microfluidic system I steer biological cells and nano particles (quantum dots) to nano meter precision. In the last part of the thesis I develop and experimentally demonstrate two dimensional (2D) manipulation of a single droplet of ferrofluid by feedback control of 4 external electromagnets, with a view towards enabling feedback control of magnetic drug delivery to reach deeper tumors in the long term. To this end, I developed and experimentally demonstrated an optimal control algorithm to effectively manipulate a single ferrofluid droplet by magnetic feedback control. This algorithm was explicitly designed to address the nonlinear and cross-coupled nature of dynamic magnetic actuation and to best exploit available electromagnetic forces for the applications of magnetic drug delivery.