This thesis presents biomimetic control of an anthropomorphic artificial finger actuated by three antagonistic shape memory alloy (SMA) muscle pairs that are each configured in a dual spring-biased configuration. This actuation system forms the basis for biomimetic tendon-driven flexion/extension of the metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints of the artificial finger, as well as the abduction/adduction of its MCP joint. This work focuses on the design and experimental verification of a new fuzzy pulse-width-modulated proportional-integral-derivative (i.e. fuzzy PWM-PID) controller that is capable of realizing cocontraction of the SMA muscle pairs, as well as online tuning of the PID gains to deal with system nonlinearities and parameter uncertainties. One of the main purposes of this thesis is the proposed biomimetic cocontraction control strategy, which co-activates the antagonistic muscle pairs as a synergistic functional unit. It emulates a similar strategy in neural control, called “common drive,” employed by the central nervous system (CNS). In order to maintain a desired position of a joint, the corresponding agonistic muscle pairs are cocontracted by the CNS and numerical simulations using a dynamic model of the system. The performance advantage of the cocontracting fuzzy PWM-PID controller over the original PWM-PID controller is shown by experimental results. A successful application of the new controller to fingertip trajectory tracking tasks using the MCP joint’s flexion/extension and abduction/adduction is also described. Since commercially available SMA actuators used for artificial muscle pairs have limited stroke, a new compact design was considered to increase the stroke of SMA actuators with similar power capacity. The design and fabrication process of the new SMA actuators are described followed by preliminary testing of the actuators’ performance as artificial muscle pairs with the designed fuzzy PWM-PID control algorithm.