Permanent magnet linear synchronous motors (PMLSMs) play a vital role in a variety of applications, from their use as components in mechatronic systems to generate linear motion to industrial manufacturing and transportation systems, as well as passenger transport, such as magnetically levitated vehicles (MAGLEVs). In particular, PMLSMs have gained significant attention in industrial transportation systems due to their high performance and unique ability to transport multiple products independently using a single motor setup. Moreover, motor designs featuring a segmented stator with different stator geometries significantly enhance the flexibility of PMLSMs. This work considers a segmented stator PMLSM with different segment types, each featuring a different curvature, enabling the realization of complex motor setups. As a basis for analysis, simulation, and controller design, a highly accurate and computationally efficient mathematical model of the curved motor segments is developed, building upon an existing model for straight segments (which do not exhibit a curvature). The model systematically accounts for nonlinear effects such as saturation and cogging forces and can be calibrated with measurements to further improve its accuracy. The high accuracy of the model is validated through test bench measurements, confirming high accuracy in both the force and the magnetic quantities. In order to control the movement of the shuttles, this work presents a control strategy consisting of a subordinate force controller and a superimposed position controller. The force controller is implemented as a current controller, where optimal currents, computed based on the highly accurate mathematical model, are applied, enabling an indirect force control strategy since no direct force measurement is available. The motor setup features many coils within each segment, introducing multiple degrees of freedom. By using an optimization approach to obtain the coil currents, these degrees of freedom can be utilized not only to generate a specific tractive force on a shuttle but also to pursue objectives such as minimizing the ohmic losses or reducing the load on specific electrical components, such as a voltage balancer, by minimizing the sum current.In typical industrial transportation applications, the moving units (shuttles or movers) execute position-controlled movements. Since smooth and accurate shuttle motion is vital, especially for applications that involve on-the-move processing, a highly precise position measurement is required. In the considered PMLSM, anisotropic magnetoresistive (AMR) sensors are employed to measure the shuttles' positions by detecting the magnetic field direction of the permanent magnets (PMs) mounted on the shuttles as they pass by the sensors. Tolerances in the sensor mounting, the sensor electronics, and the magnetization of the PMs affect the position measurement and can result in intolerably high position errors if the sensor system is not calibrated properly. To address this, the present work proposes a user-friendly and cost-effective online calibration method utilizing iterative learning. The method is validated on a test bench, showing its effectiveness and robustness against shuttle wear and mounting, as well as manufacturing tolerances.Based on a mechanical model of the shuttle, a position controller is designed as a superimposed control loop. When combined with the optimal force control strategy, the position controller achieves high position-tracking accuracy within the segments. However, due to the segmented stator design, larger disturbances, and thus larger position errors, occur at segment transitions, where the shuttle moves from one segment to another. No highly accurate model is available for these regions, as the disturbances strongly depend on manufacturing, mounting, and assembly tolerances introduced during the final assembly of the motor setup at the customer's site. Consequently, exact modeling of these transitions is not feasible with sufficient accuracy. Manufacturing tolerances also affect tracking accuracy within the segments, albeit to a lesser extent. To account for these model-plant mismatches, a learning-based feedforward force compensation is proposed to achieve high-precision position tracking over the entire curvilinear track of the segmented stator PMLSM. The method is validated on a test bench, demonstrating its effectiveness. Moreover, a comparison with state-of-the-art control strategies reveals a significant increase in motor efficiency when using the proposed method. Additionally, experiments confirm that the approach is robust to shuttle variations and wear, ensuring high tracking performance across all industrially relevant cases.Typically, multiple shuttles operate on the motor simultaneously. To maximize throughput and thereby increase productivity, shuttles must operate in close proximity, enabling high-density transport of products. However, this introduces additional challenges due to interactions between shuttles as the inter-shuttle distance decreases. This work extends the control strategy developed for the single-shuttle operation to multiple shuttles. The same high-precision position tracking performance achieved for single-shuttle operation is maintained along the entire motor track, even when shuttles operate in close proximity, ensuring efficient and collision-free operation in high-throughput applications.