Therapies using functional electrical stimulation (FES) in conjunction with practice of everyday tasks have proven effective in facilitating recovery of upper limb function following stroke. The aim of the current study is to develop a multi-channel electrical stimulation system that precisely controls the assistance provided in goal-orientated tasks through use of advanced model-based 'iterative learning control' (ILC) algorithms to facilitate functional motor recovery of the upper limb post-stroke. FES was applied to three muscle groups in the upper limb (the anterior deltoid, triceps and wrist extensors) to assist hemiparetic, chronic stroke participants to perform a series of functional tasks with real objects, including closing a drawer, turning on a light switch and repositioning an object. Position data from the participants' impaired upper limb was collected using a Microsoft Kinect® and was compared to an ideal reference. ILC used data from previous attempts at the task to moderate the FES signals applied to each muscle group on a trial by trial basis to reduce performance error whilst supporting voluntary effort by the participant. The clinical trial is on-going. Preliminary results show improvements in performance accuracy for each muscle group, as well as improvements in clinical outcome measures pre and post 18 training sessions. Thus, the feasibility of applying precisely controlled FES to three muscle groups in the upper limb to facilitate functional reach and grasp movements post stroke has been demonstrated.