  We consider a wireless networked control system (WNCS) with bidirectional
imperfect links for real-time applications such as smart grids. To maintain the
stability of WNCS, captured by the probability that plant state violates preset
values, at minimal cost, heterogeneous physical processes are monitored by
multiple sensors. This status information, such as dynamic plant state and
Markov Process-based context information, is then received/estimated by the
controller for remote control. However, scheduling multiple sensors and
designing the controller with limited resources is challenging due to their
coupling, delay, and transmission loss. We formulate a Constrained Markov
Decision Problem (CMDP) to minimize violation probability with cost
constraints. We reveal the relationship between the goal and different updating
actions by analyzing the significance of information that incorporates
goal-related usefulness and contextual importance. Subsequently, a
goal-oriented deterministic scheduling policy is proposed. Two sensing-assisted
control strategies and a control-aware estimation policy are proposed to
improve the violation probability-cost tradeoff, integrated with the scheduling
policy to form a goal-oriented co-design framework. Additionally, we explore
retransmission in downlink transmission and qualitatively analyze its
preference scenario. Simulation results demonstrate that the proposed
goal-oriented co-design policy outperforms previous work in simultaneously
reducing violation probability and cost
