We present TALplanner, a forward-chaining planner based on the use of domain-dependent search control knowledge represented as temporal formulas in the Temporal Action Logic (TAL). TAL is a narrative based linear metric time logic used for reasoning about action and change in incompletely specified dynamic environments. TAL is used as the formal semantic basis for TALplanner, where a TAL goal narrative with control formulas is input to TALplanner which then generates a TAL narrative that entails the goal formula. We extend the sequential version of TALplanner, which has previously shown impressive performance on standard benchmarks, in two respects: 1) TALplanner is extended to generate concurrent plans, where operators have varied durations and internal state; and 2) the expressiveness of plan operators is extended for dealing with several different types of resources. The extensions to the planner have been implemented and concurrent planning with resources is demonstrated using an extended logistics benchmark.